Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers.

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

The biomarker-based diagnosis of Alzheimer's disease. 2-lessons from oncology.

Biomarkers for the diagnosis of Alzheimer's disease (AD) are not yet validated for use in clinical settings. We aim to provide a methodological framework for their systematic validation, by reference to that developed for oncology biomarkers. As for this discipline, the steps for the systematic validation of AD biomarkers need to target analytical validity, clinical validity, and clinical utility. However, the premises are different from oncology: the nature of disease (neurodegeneration vs. cancer), the purpose (improve diagnosis in clinically affected vs. screening preclinical individuals), and the target population (mild cognitive impairment patients referring to memory clinics vs. general population) lead to important differences, influencing both the design of validation studies and the use of selected biomarkers. This framework is applied within a wider initiative to assess the current available evidence on the clinical validity of biomarkers for AD, for the final aim to identify gaps and research priorities, and to inform coordinated research efforts boosting AD biomarkers research.

Personality traits and risk of cognitive impairment and dementia.

We investigated the association between five factor model personality traits (neuroticism, extraversion, openness, agreeableness, and conscientiousness) and risk of dementia, cognitive impairment not dementia (CIND), and conversion from CIND to dementia in a large national cohort. Participants from the Health and Retirement Study (N > 10,000) completed a personality scale in 2006-2008 and their cognitive status was tracked for up to 8 years using the modified Telephone Interview for Cognitive Status (TICSm). Adjusting for age, sex, education, race, and ethnicity, lower conscientiousness and agreeableness and higher neuroticism were independently associated with increased risk of dementia. These associations remained significant after adjusting for other risk factors for dementia, including income, wealth, smoking, physical inactivity, obesity, diabetes, hypertension, and blood biomarkers. These associations were not modified by age, sex, race, ethnicity, and education, suggesting that the associations of personality with risk of dementia were similar across demographic groups. Neuroticism and conscientiousness were also associated with risk of CIND. Low conscientiousness predicted conversion from CIND to dementia. Using brief assessments of personality and cognition, we found robust evidence that personality is associated with risk of cognitive impairment and dementia in a large national sample.

Association Between Lifetime Marijuana Use and Cognitive Function in Middle Age: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.

IMPORTANCE: Marijuana use is increasingly common in the United States. It is unclear whether it has long-term effects on memory and other domains of cognitive function. OBJECTIVE: To study the association between cumulative lifetime exposure to marijuana use and cognitive performance in middle age. DESIGN, SETTING, AND PARTICIPANTS: We used data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a cohort of 5115 black and white men and women aged 18 to 30 years at baseline from March 25, 1985, to June 7, 1986 (year 0), and followed up over 25 years from June 7, 1986, to August 31, 2011, to estimate cumulative years of exposure to marijuana (1 year = 365 days of marijuana use) using repeated measures and to assess associations with cognitive function at year 25. Linear regression was used to adjust for demographic factors, cardiovascular risk factors, tobacco smoking, use of alcohol and illicit drugs, physical activity, depression, and results of the mirror star tracing test (a measure of cognitive function) at year 2. Data analysis was conducted from June 7, 1986, to August 31, 2011. MAIN OUTCOMES AND MEASURES: Three domains of cognitive function were assessed at year 25 using the Rey Auditory Verbal Learning Test (verbal memory), the Digit Symbol Substitution Test (processing speed), and the Stroop Interference Test (executive function). RESULTS: Among 3385 participants with cognitive function measurements at the year 25 visit, 2852 (84.3%) reported past marijuana use, but only 392 (11.6%) continued to use marijuana into middle age. Current use of marijuana was associated with worse verbal memory and processing speed; cumulative lifetime exposure was associated with worse performance in all 3 domains of cognitive function. After excluding current users and adjusting for potential confounders, cumulative lifetime exposure to marijuana remained significantly associated with worse verbal memory. For each 5 years of past exposure, verbal memory was 0.13 standardized units lower (95% CI, -0.24 to -0.02; P = .02), corresponding to a mean of 1 of 2 participants remembering 1 word fewer from a list of 15 words for every 5 years of use. After adjustment, we found no associations with lower executive function (-0.03 [95% CI, -0.12 to 0.07]; P = .56) or processing speed (-0.04 [95% CI, -0.16 to 0.08]; P = .51). CONCLUSIONS AND RELEVANCE: Past exposure to marijuana is associated with worse verbal memory but does not appear to affect other domains of cognitive function.

Weight loss and premature death: the 1946 British birth cohort study.

OBJECTIVE: The relationship between weight loss and mortality has important clinical and public health significance but has proved to be complex. Evidence is mixed and particularly limited on the association between weight loss in mid-life and premature death (i.e. before 65 years of age), a small albeit important segment of total mortality. We aimed to study the association between midlife weight change and mortality accounting for health and lifestyle characteristics, and also considering potential bias due to preexisting chronic diseases and smoking status. DESIGN: Longitudinal, population-based, 'the 1946 British' birth cohort study. SUBJECTS AND MEASURES: In 2750 men and women, mortality from age 53 through 65 years was analyzed according to categories of measured 10 year weight change between 43 and 53 years. Cox's hazard ratios (HR) were progressively adjusted for socio-demographic, lifestyle and health characteristics. RESULTS: Nearly 20% of participants lost weight and over 50% gained 5 kg or more in midlife. There were 164 deaths. Compared to those who gained between 2 and 5 kg, those who lost 5 kg or more had an increased risk of premature death independently of midlife physical activity, socio-economic circumstances and educational attainment. This association was unaltered when highest weight loss (lost more than 15 Kg) (p = 0.04) and early deaths were excluded (p<0.001), but was no longer significant after adjustment for cardiovascular risk factors and health status (HR = 1.8; 95% CI: 0.9 to 3.5). CONCLUSION: The inverse association between weight loss in midlife and higher risk of premature death may be explained by vascular risk factors and ill health. In consideration of the burden of premature death, closer monitoring of weight loss in mid-life is warranted.