Objectives: It is still a matter of debate whether variables such as education, sex, age, personality and others underlie subjective memory complaints (SMC). Our objectives are to study: the prevalence of memory complaints in the city of Madrid, the distribution of complaints in the population according to socio-demographic variables and the related variables like cognitive performance, quality of life, perceived health status and functional ability. To our knowledge, this is the first study about the prevalence of SMC in Spain. Methods: We adopted a transversal descriptive epidemiological study. The survey sample size is 1637 persons above 64 years. SMC were obtained through questions regarding memory complaints. Results: 524 (32.4%) subjects reported SMC. The prevalence of SMC depends on age, education, sex, mood and cognitive performance. SMC rises from 24% in the 65–69 age groups to 57% in the 90 and above group. The percentage of subjects with SMC was 52.8% among persons diagnosed with depression or anxiety, and 28.7% among subjects without. Performance on cognitive tests such as orientation showed that subjects without orientation failures (81%) have a 22.2% SMC frequency and subjects who fail all the orientation items (4%) have a 93% frequency. A logistic regression analysis showed that those variables indicating a better prediction of group membership (SMC vs. controls) were orientation in time, quality of life and depression–anxiety. Conclusion: Complaints reflect various processes and are the result of various elements; however, our study highlights the importance of factors such as cognitive performance, depression–anxiety and quality of life.

Alzheimer’s Disease is a complex, multifactorial, and comorbid condition. The asymptomatic behavior in the early stages makes the identification of the disease onset particularly challenging. Mild cognitive impairment (MCI) is an intermediary stage between the expected decline of normal aging and the pathological decline associated with dementia. The identification of risk factors for MCI is thus sorely needed. Self-reported personal information such as age, education, income level, sleep, diet, physical exercise, etc. is called to play a key role not only in the early identification of MCI but also in the design of personalized interventions and the promotion of patients empowerment. In this study, we leverage a large longitudinal study on healthy aging in Spain, to identify the most important self-reported features for future conversion to MCI. Using machine learning (random forest) and permutation-based methods we select the set of most important self-reported variables for MCI conversion which includes among others, subjective cognitive decline, educational level, working experience, social life, and diet. Subjective cognitive decline stands as the most important feature for future conversion to MCI across different feature selection techniques.

These authors contributed equally to this work. Background: Alzheimer’s disease (AD) is a silent disorder that needs the earliest possible intervention in order to reduce its high economic and social impact. It has been recently suggested that subjec

The MAPT H1 haplotype has been linked to several disorders, but its relationship with Alzheimer’s disease (AD) remains controversial. A rare variant in MAPT (p.A152T) has been linked with frontotemporal dementia (FTD) and AD. We genotyped H1/H2 and p.A152T MAPT in 11,572 subjects from Spain (4,327 AD, 563 FTD, 648 Parkinson’s disease (PD), 84 progressive supranuclear palsy (PSP), and 5,950 healthy controls). Additionally, we included 101 individuals from 21 families with genetic FTD. MAPT p.A152T was borderline significantly associated with FTD [odds ratio (OR) = 2.03; p = 0.063], but not with AD. MAPT H1 haplotype was associated with AD risk (OR = 1.12; p = 0.0005). Stratification analysis showed that this association was mainly driven by APOE ɛ4 noncarriers (OR = 1.14; p = 0.0025). MAPT H1 was also associated with risk for PD (OR = 1.30; p = 0.0003) and PSP (OR = 3.18; p = 8.59 × 10-8) but not FTD. Our results suggest that the MAPT H1 haplotype increases the risk of PD, PSP, and non-APOE ɛ4 AD.