Practical guidelines for the preparation of tissue sections for direct analysis by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry are presented. Techniques for proper sample handling including tissue storage, sectioning and mounting are described. Emphasis is placed on optimizing matrix parameters such as the type of matrix molecule used, matrix concentration, and solvent composition. Several different techniques for matrix application are illustrated. Optimal instrument parameters and the necessity for advanced data analysis approaches with regards to direct tissue analysis are also discussed.

MALDI (matrix-assisted laser desorption/ionization) imaging mass spectrometry (IMS) is a new technology that generates molecular profiles and two-dimensional ion density maps of peptide and protein signals directly from the surface of thin tissue sections. This allows specific information to be obtained on the relative abundance and spatial distribution of proteins. One important aspect of this is the opportunity to correlate these specific ion images with histological features observed by optical microscopy. To facilitate this, we have developed protocols that allow MALDI mass spectrometry imaging and optical microscopy to be performed on the same section. Key components of these protocols involve the use of conductive glass slides as sample support for the tissue sections and MS-friendly tissue staining protocols. We show the effectiveness of these with protein standards and with several types of tissue sections. Although stain-specific intensity variations occur, the overall protein pattern and spectrum quality remain consistent between stained and control tissue samples. Furthermore, imaging mass spectrometry experiments performed on stained sections showed good image quality with minimal delocalization of proteins resulting from the staining protocols.

Objectives-Progression of Alzheimer's dementia (AD) is highly variable. Most estimates derive from convenience samples from dementia clinics or research centers where there is substantial potential for survival bias and other distortions. In a population-based sample of incident AD cases, we examined progression of impairment in cognition, function, and neuropsychiatric symptoms, and the influence of selected variables on these domains. Design-Longitudinal, prospective cohort study Setting-Cache County (Utah)Participants-328 persons diagnosed with Possible/Probable AD Measurements-Mini-Mental State Exam (MMSE), Clinical Dementia Rating sum-of-boxes (CDR-sb), and Neuropsychiatric Inventory (NPI).Results-Over a mean follow-up of 3.80 (range 0.07-12.90) years, the mean (S.D.) annual rates of change were −1.53 (2.69) on the MMSE, 1.44 (1.82) on the CDR-sb, and 2.55 (5.37) scale points on the NPI. Among surviving participants, 30-58% progressed less than one point/year on these measures, even 5-7 years after dementia onset. Rates of change were correlated between MMSE and CDR-sb (r=−0.62, df=201, p<0.001) and between the CDR-sb and NPI (r=0.20, df=206, p<0.004). Females (LR χ 2 =8.7, df=2, p=0.013) and those with younger onset (LR χ 2 =5.7, df=2, p=0.058) declined faster on the MMSE. Although one or more APOE ε4 alleles and ever-use of FDA-approved anti-dementia medications were associated with initial MMSE scores, neither was related to the rate of progression in any domain.Conclusions-A significant proportion of persons with AD progresses slowly. The results underscore differences between population-vs. clinic-based samples and suggest ongoing need to identify factors that may slow the progression of AD. KeywordsAlzheimer's disease; dementia; cognition; neuropsychiatric symptoms; progression; decline Alzheimer's dementia (AD) is a significant cause of disability and mortality among the elderly. Some 26.6 million cases presently worldwide may increase to 106.2 million by 2050,(1) unless a means of prevention can be identified. Without a cure, better understanding of the clinical course and course-modifying factors is needed.AD causes impairment not only in cognition and function, but also in behavior prompted by neuropsychiatric symptoms (NPS). Numerous studies report significant variability in the rate of cognitive and functional decline in AD. For example, a recent review reported that the mean annual rate of change (ARC) on the Mini-Mental State Exam (MMSE), a global measure of cognition, varied from 0.8 to 4.4 points.(2) Similar variability is seen in functional decline,(3) although comparisons across studies are impeded by differences in instrumentation. NPS in AD are marked by increasing incidence over time and by an episodic course. (4) These studies of the natural history of AD share several limitations. Most come from observations in clinics or clinical research centers. Compared to panels of AD cases ascertained from populations, clinic AD patients are up to 20 years younger, have higher Here, we d...

Objective Little is known about factors influencing the rate of progression of Alzheimer’s dementia. Using data from the Cache County Dementia Progression Study, we examined the link between clinically significant neuropsychiatric symptoms in mild Alzheimer’s dementia and progression to severe dementia or death. Method The Cache County Dementia Progression Study is a longitudinal study of dementia progression in incident cases of the condition. Survival analyses included unadjusted Kaplan-Meier plots and multivariate Cox proportional hazard models. Hazard ratio estimates controlled for age of dementia onset, dementia duration at baseline, gender, education level, General Medical Health Rating, and apolipoprotein E epsilon 4 (APOE-ε4) genotype. Results Three hundred thirty-five patients with incident Alzheimer’s dementia were studied. Sixty-eight (20%) developed severe dementia over the follow-up. Psychosis (hazard ratio=2.007, p=0.028), agitation/aggression (hazard ratio=2.946, p=0.004), and any one clinically significant neuropsychiatric symptom (domain score of ≥4, hazard ratio=2.682, p=0.001) were associated with more rapid progression to severe dementia. Psychosis (hazard ratio=1.537, p=0.011), affective symptoms (hazard ratio=1.510, p=0.003), agitation/aggression (hazard ratio=1.942, p=0.004), mildly symptomatic neuropsychiatric symptoms (domain score of 1–3, hazard ratio=1.448, p=0.024), and clinically significant neuropsychiatric symptoms (hazard ratio=1.951, p=<0.001) were associated with earlier death. Conclusions Specific neuropsychiatric symptoms are associated with shorter survival time from mild Alzheimer’s dementia to severe dementia and/or death. The treatment of specific neuropsychiatric symptoms in mild Alzheimer’s dementia should be examined for its potential to delay time to severe dementia or death.

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Clinical diagnosis and treatment decisions for a subset of primary human brain tumors, gliomas, are based almost exclusively on tissue histology. Approaches for glioma diagnosis can be highly subjective due to the heterogeneity and infiltrative nature of these tumors and depend on the skill of the neuropathologist. There is therefore a critical need to develop more precise, nonsubjective, and systematic methods to classify human gliomas. To this end, mass spectrometric analysis has been applied to these tumors to determine glioma-specific protein patterns. Protein profiles have been obtained from human gliomas of various grades through direct analysis of tissue samples using matrix-assisted laser desorption ionization mass spectrometry (MS). Statistical algorithms applied to the MS profiles from tissue sections identified protein patterns that correlated with tumor histology and patient survival. Using a data set of 108 glioma patients, two patient populations, a short-term and a long-term survival group, were identified based on the tissue protein profiles. In addition, a subset of 57 patients diagnosed with high-grade, grade IV, malignant gliomas were analyzed and a novel classification scheme that segregated short-term and long-term survival patients based on the proteomic profiles was developed. The protein patterns described served as an independent indicator of patient survival. These results show that this new molecular approach to monitoring gliomas can provide clinically relevant information on tumor malignancy and is suitable for high-throughput clinical screening. (Cancer Res 2005; 65(17): 7674-81)

Objective To determine whether baseline hearing loss increases cognitive decline and risk for all-cause dementia in a population of elderly individuals. Study design Longitudinal cohort study Setting Community-based, outpatient Patients Men and women aged 65 years or older without dementia at baseline Intervention(s) All subjects completed the Modified Mini-Mental Status Exam (3MS-R) at baseline and over 3 triennial follow-up visits. Hearing loss (HL) at baseline was based on observation of hearing difficulties during testing or interview. Incident dementia was determined by clinical assessment and expert consensus. Main outcome measure(s) Dementia and 3MS-R score. Results At baseline 4,463 subjects were without dementia, 836 of whom had HL. Of those with HL, 16.3% developed dementia, compared to 12.1% of those without HL (p<0.001). Mean time to dementia was 10.3 years in the HL group vs. 11.9 years for non-HL (Log Rank test p<0.001). In Cox regression analyses controlling for gender, presence of APOE- ε4 allele, education, and baseline age, and cardiovascular risk factors, HL was an independent predictor of developing dementia (Hazard ratio = 1.27, p=0.026 (95% CI = 1.03, 1.56). Linear mixed models controlling for similar covariates showed HL was associated with faster decline on the 3MS-R, at a rate of 0.26 points/year worse than those without HL. Conclusions Elderly individuals with HL have an increased rate of developing dementia and more rapid decline on 3MS-R scores than their non-hearing impaired counterparts. These findings suggest that hearing impairment may be a marker for cognitive dysfunction in adults age 65 and older.

Purpose: The purpose of this research was to perform a preliminary assessment of protein patterns in primary brain tumors using a direct-tissue mass spectrometric technique to profile and map biomolecules.Experimental Design: We examined 20 prospectively collected, snap-frozen normal brain and brain tumor specimens using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS), and compared peptide and protein expression in primary brain tumor and nontumor brain tissues.Results: MS can be used to identify protein expression patterns in human brain tissue and tumor specimens. The mass spectral patterns can reliably identify glial neoplasms of similar histological grade and differentiate them from tumors of different histological grades as well as from nontumor brain tissues. Initial bioinformatics cluster analysis algorithms classified tumor and nontumor tissues into similar groups comparable with their histological grade.Conclusions: We describe a novel tool for the analysis of protein expression patterns in human glial neoplasms. Initial results demonstrate that MALDI-MS technology can significantly aid in the process of unraveling and understanding the molecular complexities of gliomas. MALDI-MS accurately and reliably identified normal and neoplastic tissues, and could be used to discriminate between tumors of increasing grades.