本报告汇总了阿尔茨海默病及痴呆相关领域现有的最新数据， 分析了我国阿尔茨海默病的流行病学、疾病负担、诊断治疗、风险因素、康复护理和疾病筛查等各方面的现状、问题以及趋势，针对目前中国民众和政策制定者最关心的问题，例如：阿尔茨海默病基本数据是怎样的?为什么知晓率相对提高，但是患者就诊愿望相对不高?如何采用有效的措施来应对，等等，提出了目前阿尔茨海默病的防控策略。特别强调了要大力开发经过验证的早期筛查和诊断工具，提供更有效治疗的创新药物，以及鼓励和建立全国性属地化社会互助支持网络。本报告期望能对医学专业人士、患者、家属和照护者、政府政策制定人员、养老机构等有所帮助，能为阿尔茨海默病的防治工作提供支撑，为相关卫生政策的制定提供依据和建议，有助于提高公众对阿尔茨海默病的认识，以期缓解我国阿尔茨海默病疾病的整体负担，推动我国健康老龄化的实现。

Recent estimates suggesting that over half of Alzheimer's disease burden worldwide might be attributed to potentially modifiable risk factors do not take into account risk-factor non-independence. We aimed to provide specific estimates of preventive potential by accounting for the association between risk factors.Using relative risks from existing meta-analyses, we estimated the population-attributable risk (PAR) of Alzheimer's disease worldwide and in the USA, Europe, and the UK for seven potentially modifiable risk factors that have consistent evidence of an association with the disease (diabetes, midlife hypertension, midlife obesity, physical inactivity, depression, smoking, and low educational attainment). The combined PAR associated with the risk factors was calculated using data from the Health Survey for England 2006 to estimate and adjust for the association between risk factors. The potential of risk factor reduction was assessed by examining the combined effect of relative reductions of 10% and 20% per decade for each of the seven risk factors on projections for Alzheimer's disease cases to 2050.Worldwide, the highest estimated PAR was for low educational attainment (19·1%, 95% CI 12·3-25·6). The highest estimated PAR was for physical inactivity in the USA (21·0%, 95% CI 5·8-36·6), Europe (20·3%, 5·6-35·6), and the UK (21·8%, 6·1-37·7). Assuming independence, the combined worldwide PAR for the seven risk factors was 49·4% (95% CI 25·7-68·4), which equates to 16·8 million attributable cases (95% CI 8·7-23·2 million) of 33·9 million cases. However, after adjustment for the association between the risk factors, the estimate reduced to 28·2% (95% CI 14·2-41·5), which equates to 9·6 million attributable cases (95% CI 4·8-14·1 million) of 33·9 million cases. Combined PAR estimates were about 30% for the USA, Europe, and the UK. Assuming a causal relation and intervention at the correct age for prevention, relative reductions of 10% per decade in the prevalence of each of the seven risk factors could reduce the prevalence of Alzheimer's disease in 2050 by 8·3% worldwide.After accounting for non-independence between risk factors, around a third of Alzheimer's diseases cases worldwide might be attributable to potentially modifiable risk factors. Alzheimer's disease incidence might be reduced through improved access to education and use of effective methods targeted at reducing the prevalence of vascular risk factors (eg, physical inactivity, smoking, midlife hypertension, midlife obesity, and diabetes) and depression.National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care for Cambridgeshire and Peterborough.Copyright © 2014 Elsevier Ltd. All rights reserved.

The aetiology of Alzheimer's disease (AD) is believed to involve environmental exposure and genetic susceptibility. The aim of our present systematic review and meta-analysis was to roundly evaluate the association between AD and its modifiable risk factors.We systematically searched PubMed and the Cochrane Database of Systematic Reviews from inception to July 2014, and the references of retrieved relevant articles. We included prospective cohort studies and retrospective case-control studies.16,906 articles were identified of which 323 with 93 factors met the inclusion criteria for meta-analysis. Among factors with relatively strong evidence (pooled population >5000) in our meta-analysis, we found grade I evidence for 4 medical exposures (oestrogen, statin, antihypertensive medications and non-steroidal anti-inflammatory drugs therapy) as well as 4 dietary exposures (folate, vitamin E/C and coffee) as protective factors of AD. We found grade I evidence showing that one biochemical exposure (hyperhomocysteine) and one psychological condition (depression) significantly increase risk of developing AD. We also found grade I evidence indicative of complex roles of pre-existing disease (frailty, carotid atherosclerosis, hypertension, low diastolic blood pressure, type 2 diabetes mellitus (Asian population) increasing risk whereas history of arthritis, heart disease, metabolic syndrome and cancer decreasing risk) and lifestyle (low education, high body mass index (BMI) in mid-life and low BMI increasing the risk whereas cognitive activity, current smoking (Western population), light-to-moderate drinking, stress, high BMI in late-life decreasing the risk) in influencing AD risk. We identified no evidence suggestive of significant association with occupational exposures.Effective interventions in diet, medications, biochemical exposures, psychological condition, pre-existing disease and lifestyle may decrease new incidence of AD.Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The association between body mass index (BMI) and Alzheimer's disease (AD) remains controversial. Genetic and environmental factors are now considered contributors to AD risk. However, little is known about the potential interaction between genetic risk and BMI on AD risk.To study the causal relationship between BMI and AD, and the potential interaction between AD genetic risk and BMI on AD risk.Using the UK Biobank database, 475,813 participants were selected for an average follow-up time of more than 10 years.1) there was a nonlinear relationship between BMI and AD risk in participants aged 60 years or older (p for non-linear < 0.001), but not in participants aged 37-59 years (p for non-linear = 0.717) using restricted cubic splines; 2) for participants aged 60 years and older, compared with the BMI (23-30 kg/m) group, the BMI (< 23 kg/m) group was associated with a higher AD risk (HR = 1.585; 95% CI 1.304-1.928, p < 0.001) and the BMI (> 30 kg/m) group was associated with a lower AD risk (HR = 0.741; 95% CI 0.618-0.888, p < 0.01) analyzed using the Cox proportional risk model; 3) participants with a combination of high AD genetic risk score (AD-GRS) and BMI (< 23 kg/m) were associated with the highest AD risk (HR = 3.034; 95% CI 2.057-4.477, p < 0.001). In addition, compared with the BMI (< 23 kg/m), the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD-GRS; 4) there was a reverse causality between BMI and AD when analyzed using bidirectional Mendelian randomization (MR).There was a reverse causality between BMI and AD analyzed using MR. For participants aged 60 years and older, the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD genetic risk. BMI (23-30 kg/m) may be a potential intervention for AD.© 2022. The Author(s).

This study aims to investigate the association between trajectories of the cognition and body mass index (BMI) among Chinese middle and old-aged adults. A total of 5693 adults (age 45 +) whose cognitive score is higher than average at the baseline were included from China Health and Retirement Longitudinal Study (CHARLS:2011-2015). Cognitive function was measured by Mini-mental state examination (MMSE) in Chinese version. The Group-based trajectory modeling (GBTM) was adopted to identify the potential heterogeneity of longitudinal changes over the past 5 years and to investigate the relationship between baseline BMI and trajectories of cognitive function. Three trajectories were identified in results: the slow decline (37.92%), the rapid decline (6.71%) and the stable function (55.37%). After controlling for other variables, underweight (BMI < 18.5 kg/m) was associated with the rapid and slow decline trajectories. Obesity (BMI > 28 kg/m) was associated with the slow decline trajectory. High-risk people of cognitive decline can be screened by measuring BMI.© 2022. The Author(s).

The amygdala -- an almond-shaped group of nuclei at the heart of the telencephalon -- has been associated with a range of cognitive functions, including emotion, learning, memory, attention and perception. Most current views of amygdala function emphasize its role in negative emotions, such as fear, and in linking negative emotions with other aspects of cognition, such as learning and memory. However, recent evidence supports a role for the amygdala in processing positive emotions as well as negative ones, including learning about the beneficial biological value of stimuli. Indeed, the amygdala's role in stimulus-reward learning might be just as important as its role in processing negative affect and fear conditioning.

Recent research on the nucleus accumbens (NA) indicates that this brain region is involved in learning and memory processes in a way that is separable from its other well-known roles in behavior, such as motivation, reward, and locomotor activity. These findings have suggested that 1) the NA may be involved in declarative, or hippocampal formation-dependent learning and memory, and not in several other non-declarative forms of learning and memory, and 2) the NA may be selectively involved in certain stages of learning and memory. These characteristics suggest that the NA may be part of a larger striatal system which subserves acquisition and consolidation, but is not a site of long-term storage, of different forms of learning and memory.

The basal ganglia as a whole are broadly responsible for sensorimotor coordination, including response selection and initiation. However, it has become increasingly clear that regions of the basal ganglia are functionally delineated along corticostriatal lines, and that a modular conception of the respective functions of various nuclei is useful. Here we examine the specific role of the caudate nucleus, and in particular, how this differs from that of the putamen. This review considers converging evidence from multiple domains including anatomical studies of corticostriatal circuitry, neuroimaging studies of healthy volunteers, patient studies of performance deficits on a variety of cognitive tests, and animal studies of behavioural control. We conclude that the caudate nucleus contributes to behaviour through the excitation of correct action schemas and the selection of appropriate sub-goals based on an evaluation of action-outcomes; both processes fundamental to successful goal-directed action. This is in contrast to the putamen, which appears to subserve cognitive functions more limited to stimulus-response, or habit, learning. This modular conception of the striatum is consistent with hierarchical models of cortico-striatal function through which adaptive behaviour towards significant goals can be identified (motivation; ventral striatum), planned (cognition; caudate) and implemented (sensorimotor coordination; putamen) effectively.

The ability to resist the urge to eat requires the proper functioning of neuronal circuits involved in top-down control to oppose the conditioned responses that predict reward from eating the food and the desire to eat the food. Imaging studies show that obese subjects might have impairments in dopaminergic pathways that regulate neuronal systems associated with reward sensitivity, conditioning and control. It is known that the neuropeptides that regulate energy balance (homeostatic processes) through the hypothalamus also modulate the activity of dopamine cells and their projections into regions involved in the rewarding processes underlying food intake. It is postulated that this could also be a mechanism by which overeating and the resultant resistance to homoeostatic signals impairs the function of circuits involved in reward sensitivity, conditioning and cognitive control.Published by Elsevier Ltd.

We aimed to investigate the relationship between BMI (body mass index) and the volumes of the structures of the reward system (hippocampus, amygdala, accumbens, caudatum, putamen, and orbitofrontal cortex). The right and left structures were examined separately. Their volumes were assessed using a 3-T MRI scanner and Freesurfer software. Ninety-two healthy subjects were involved (mean BMI: 22.3 ± 3.4 kg/m(2), mean age: 23.2 ± 2.7). We found that the volume of the right amygdala positively correlated with the BMI in men but not in women. Moreover, we could demonstrate this association only in the overweight male sub-population. We suggest that an association between body weight and the morphological variability of the reward system can be demonstrated by MRI. This may be further evidence for a different body-weight regulation in the two sexes. The potential relationship between the volume of the right amygdala and the BMI in heavier individuals requires further studies with larger samples.

Overweight and obesity are rapidly becoming a central public health challenge around the world. Previous studies have suggested that elevated Body Mass Index (BMI) might be associated with structural changes in both gray and white matter, but this association is still not well understood. The present study aimed to investigate the relationship between BMI and brain structure with a relatively large sample of young adults (N = 336) in a small age range (20 ± 1 years). Voxel-based morphometry results showed significant negative correlations between BMI and gray-matter volumes in the midcingulate cortex (MCC), left orbital frontal cortex, and left ventromedial prefrontal cortex. There was also a significant negative correlation between BMI and white matter integrity as indexed by fractional anisotropy in bilateral cingulum. Further tractography analysis showed a significant negative correlation between BMI and the number of fibers passing the MCC region. Regression analysis showed that gray matter and white matter in these regions both contributed to the variance of BMI. These results remained significant even when analysis was restricted to the subjects with normal weights. Finally, we found that decision-making ability (as assessed by the Iowa Gambling Task) mediated the association between the structure of the MCC (a region responsible for impulse control and decision making) and BMI. These results shed light on the structural neural basis of weight variations.

Sensitivity to reward is a personality trait that predisposes a person to several addictive behaviors, including the presence of different risky behaviors that facilitates uncontrolled eating. However, the multifactorial nature of obesity blurs a direct relationship between the two factors. Here, we studied the brain anatomic correlates of the interaction between reward sensitivity and body mass index (BMI) to investigate whether the coexistence of high BMI and high reward sensitivity structurally alters brain areas specifically involved in the regulation of eating behavior. To achieve this aim, we acquired T1-weighted images and measured reward sensitivity using the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) and BMI in a sample of 206 adults. Results showed that reward sensitivity and BMI were not significantly correlated. However, neuroimaging results confirmed a relationship between BMI and reduced volume in the medial and lateral orbitofrontal cortex, and between reward sensitivity and lower striatum volume. Importantly, the interaction between the two factors was significantly related to the right anterior hippocampus volume, showing that stronger reward sensitivity plus a higher BMI were associated with reduced hippocampal volume. The hippocampus is a brain structure involved in the higher-order regulation of feeding behavior. Thus, a dysfunctional hippocampus may contribute to maintaining a vicious cycle that predisposes people to obesity.Copyright © 2020 Parcet, Adrián-Ventura, Costumero and Ávila.

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.Copyright © 2016 Elsevier B.V. All rights reserved.

Body mass index (BMI) trajectories before the onset of mild cognitive impairment (MCI) and during the progression from MCI to dementia remain unclear.To assess the long-term BMI trajectories preceding incident MCI and dementia and explore whether they are associated with brain pathologies.The Rush Memory and Aging Project (MAP) was an ongoing community-based cohort study. This study included cognitively intact participants aged 60 to 90 years at baseline with annual follow-up from October 1997 to December 2020 (maximum follow-up of 22 years). During the follow-up, participants underwent brain autopsies. Data were analyzed from August 2021 to February 2022 using mixed-effect models.BMI was calculated using height and weight measured at baseline and follow-ups.Incident MCI and dementia were diagnosed following standard criteria. Neuropathological assessments (including global Alzheimer disease and vascular pathology) were performed for autopsies.A total of 1390 participants (mean [SD] age, 78.4 [6.5] years; 1063 female [76.5%]) were included in the study. In the analysis of BMI trajectories before MCI (n = 939), during the follow-up (median [IQR] duration, 6 [3-9] years), 371 participants (39.5%) developed MCI, of whom 88 (23.7%) progressed to dementia. Those who developed MCI were older (mean [SD] age, 79.6 [5.9] years vs 76.9 [6.6] years), consumed less alcohol (median [IQR] consumption, 0 [0-5.8] g/day vs 1.1 [0-6.9] g/day), had a lower BMI (mean [SD], 27.2 [4.9] vs 28.2 [5.9]), and were more likely to be apolipoprotein E (APOE) ε4 carriers (89 of 371 [24.0%] vs 98 of 568 [17.3%]) compared with those who remained cognitively intact over follow-up. Those who developed dementia were older (mean [SD] age, 81.0 [5.2] years vs 79.1 [6.0] years), had a lower level of physical activity (median [IQR] activity, 1.0 [0-2.5] h/week vs 1.8 [0.2-3.8] h/week), and were more likely to be APOE ε4 carriers than those who were dementia-free (33 of 88 [37.5%] vs 56 of 283 [19.8%]). Compared with participants who remained cognitively intact, in those with incident MCI, BMI tended to decline earlier and faster. From 7 years before diagnosis, people with incident MCI had an associated significantly lower BMI (mean difference, -0.96; 95% CI, -1.85 to -0.07) than those who were cognitively intact. Among people with incident MCI, the slopes of BMI decline did not differ significantly between those who did and did not develop dementia (β, -0.03; 95% CI, -0.21 to 0.15). In the analysis of BMI trajectories before autopsy (n = 358), BMI was associated with a faster declination among participants with a high burden of global Alzheimer disease pathology (β for pathology × time highest vs lowest tertile, -0.14; 95% CI, -0.26 to -0.02) or vascular pathology (β for pathology × time2 highest vs lowest tertile, 0.02; 95% CI, 0-0.05).Results of this cohort study suggest that among cognitively intact people, significantly lower BMI occurs beginning approximately 7 years before MCI diagnosis. After MCI diagnosis, BMI declines at the same pace in people who develop dementia and those who do not. High brain pathologies may underly the BMI decline preceding dementing disorders.

Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.

In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

To examine the association of change in body mass index (BMI) with risk of Alzheimer disease (AD).Nine hundred eighteen older Catholic clergy participating in the Religious Orders Study without dementia at baseline were studied. Outcome measures were the clinical diagnosis of AD and change in cognitive function.During a mean follow-up of 5.5 years, 151 persons developed AD. BMI averaged 27.4 at baseline and declined in about half the participants. In a proportional hazards model adjusted for age, sex, and education, each 1-unit less of BMI at baseline was associated with about a 5% increase in the risk of AD (hazard ratio = 0.944; 95% CI = 0.908 to 0.981), and each 1-unit annual decline in BMI (about the 10th percentile) was associated with about a 35% increase in the risk of AD compared with a person experiencing no change in BMI (about the 50th percentile) (hazard ratio = 0.730; 95% CI = 0.625 to 0.852). The results were similar after controlling for chronic diseases and excluding persons who developed AD during the first 4 years of observation. Random effects models showed that the rate of cognitive decline increased by about 8% for each 1-unit less of BMI at baseline and declined an additional 40%/year in persons losing 1 unit of BMI/year compared with those with no change in BMI.Declining body mass index (BMI) is associated with increased risk of incident Alzheimer disease (AD). Loss of BMI may reflect pathologic processes that contribute to the subsequent development of AD.

Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimer's disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated.This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers.A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females.The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults.© 2023. The Author(s).

Neurodegenerative diseases are characterized by the progressive functional loss of neurons in the brain, causing cognitive impairment and motoneuron disability. Although multifactorial interactions are evident, nutrition plays an essential role in the pathogenesis and evolution of these diseases. A systematic literature search was performed, and the prevalence of studies evaluated the effect of the Mediterranean diet (MeDiet), nutritional support, EPA and DHA, and vitamins on memory and cognition impairment. The data showed that malnutrition and low body mass index (BMI) is correlated with the higher development of dementia and mortality. MeDiet, nutritional support, and calorie-controlled diets play a protective effect against cognitive decline, Alzheimer's disease (AD), Parkinson disease (PD) while malnutrition and insulin resistance represent significant risk factors. Malnutrition activates also the gut-microbiota-brain axis dysfunction that exacerbate neurogenerative process. Omega-3 and -6, and the vitamins supplementation seem to be less effective in protecting neuron degeneration. Insulin activity is a prevalent factor contributing to brain health while malnutrition correlated with the higher development of dementia and mortality.

There are reports of weight loss and low body mass index (BMI) in patients with AD. The mesial temporal cortex (MTC) is involved in feeding behavior and memory and is preferentially involved in AD. We studied 74 subjects, including 58 AD patients and 16 control subjects, to determine whether BMI is associated with atrophy of the MTC or other brain regions. We used MRI morphometric analysis to provide measures of regional brain atrophy. AD patients had significant brain atrophy in all measured brain regions, except the white matter, compared with normal control subjects. The MTC was the only brain region significantly associated with BMI in AD patients (r = 0.39, p = 0.003). Multiple-regression analysis indicated that addition of brain regions other than the MTC to the model did not significantly add to the prediction of BMI. We conclude that low BMI correlates best and specifically with MTC atrophy. This finding supports a connection between limbic system damage and low body weight in AD.

Neuropsychiatric symptoms (NPS) occur in nearly all patients with Alzheimer's Disease (AD). Most frequently they appear since the mild cognitive impairment (MCI) stage preceding clinical AD, and have a prognostic importance. Unfortunately, these symptoms also worsen the daily functioning of patients, increase caregiver stress and accelerate the disease progression from MCI to AD. Apathy and depression are the most common of these NPS, and much attention has been given in recent years to understand the biological mechanisms related to their appearance in AD. Although for many decades these symptoms have been known to be related to abnormalities of the dopaminergic ventral tegmental area (VTA), a direct association between deficits in the VTA and NPS in AD has never been investigated. Fortunately, this scenario is changing since recent studies using preclinical models of AD, and clinical studies in MCI and AD patients demonstrated a number of functional, structural and metabolic alterations affecting the VTA dopaminergic neurons and their mesocorticolimbic targets. These findings appear early, since the MCI stage, and seem to correlate with the appearance of NPS. Here, we provide an overview of the recent evidence directly linking the dopaminergic VTA with NPS in AD and propose a setting in which the precocious identification of dopaminergic deficits can be a helpful biomarker for early diagnosis. In this scenario, treatments of patients with dopaminergic drugs might slow down the disease progression and delay the impairment of daily living activities.