You will be presented with the abstract, introduction, and discussion section from a biomedical research article. Your task is to create a summary that a layperson can understand, capturing the essence of the research article. Keep essential scientific terms, but ensure that the language remains clear and the concepts are explained in an uncomplicated manner.

Title: High Degree of Heterogeneity in Alzheimer's Disease Progression Patterns}
Article:
Abstract:
There have been several reports on the varying rates of progression among Alzheimer's Disease( AD) patients; however, there has been no quantitative study of the amount of heterogeneity in AD. Obtaining a reliable quantitative measure of AD progression rates and their variances among the patients for each stage of AD is essential for evaluating results of any clinical study. The Global Deterioration Scale( GDS) and Functional Assessment Staging procedure( FAST) characterize seven stages in the course of AD from normal aging to severe dementia. Each GDS/FAST stage has a published mean duration, but the variance is unknown. We use statistical analysis to reconstruct GDS/FAST stage durations in a cohort of 648 AD patients with an average follow-up time of 4. 78 years. Calculations for GDS/FAST stages 4–6 reveal that the standard deviations for stage durations are comparable with their mean values, indicating the presence of large variations in the AD progression among patients. Such amount of heterogeneity in the course of progression of AD is consistent with the existence of several sub-groups of AD patients, which differ by their patterns of decline.
Introduction:
The temporal progression of Alzheimer's Disease( AD) shows a pattern of high variability, with patients transiting the stages of the disease having time-courses ranging from months to decades[1],[2]. While the biological correlates of this variability have been investigated by many groups[2]–[19], the underlying reasons for such variations remain largely uncertain. One of the challenges posed by a high variability of a temporal disease course is the difficulty in treatment efficiency assessments. For any current and future progression-delaying drug, it is important to be able to establish whether and by how much it delays the deterioration caused by AD. To this end, it is necessary to have a reliable quantification of the heterogeneity of the disease. Global Deterioration Scale( GDS) was proposed in[20] and allows professionals and caregivers to chart the decline of people with AD. While a number of scales exist, GDS is one of the most widely used instruments to stage the course of AD. It measures cognitive, behavioral and functional impairment of patients. There are a total of 7 GDS stages( from stage 1 corresponding to no impairment to stage 7 corresponding to the most severe AD). In particular, stage 4( mild AD) is characterized by patients requiring assistance in complex tasks such as handling finances, planning a dinner party etc. In GDS stage 5( moderate AD) patients require assistance in choosing proper attire. In stage 6( moderately severe AD) patients require assistance in dressing and bathing, and start experiencing urinary and fecal incontinence. GDS has been shown to correlate with both behavioral measures, and anatomic brain changes[20]. Functional Assessment Staging procedure( FAST) was proposed in Ref.[21],[22]. Based on GDS, this procedure describes a continuum of 16 successive stages and substages from normality to most severe dementia of the AD type. The FAST stages have been enumerated to be concordant with the GDS stages from which they were derived[23], although some differences between the two scales have also been demonstrated[24]. One of the advantages of GDS/FAST staging system is that it allows the assessment and staging of AD in its entire range from normal aging to very severe, end-stage, AD[25]. In the literature, the course of AD as characterized by GDS/FAST staging system has been described in quantitative terms. In particular, the stages are thought to follow in a sequential fashion and are characterized by certain stage durations[26]. For example, stage 4 is thought to last for 2 years, to be followed by stage 5 whose duration is 1. 5 years, which in turn is followed by stage 6( 2. 5 years). While this quantification is a useful diagnostic tool, it reflects the average course of the disease and provides no information about possible heterogeneity of AD progression. At the same time, quantifying the variance of GDS/FAST stage durations is essential, as one needs to compare the delay gained by a treatment strategy with the amount of natural variation in stage durations, to be able to judge whether there is significance to any improvements observed. In this paper we investigate the heterogeneity of AD by studying the distribution of GDS/FAST stage durations of AD patients. We ask: how much variability is there in the course of AD, and how well do the average values for GDS/FAST stage durations reflect the disease course of individual patients?
Discussion:
Analysis of a large longitudinal dataset has revealed a significant degree of variation in the lengths of GDS/FAST stages 4–6 of AD. In particular, the calculated standard deviations for GDS/FAST stage durations turned out to have values similar to their mean durations. This is an indication that the patterns of cognitive and functional decline vary significantly from patient to patient. The suggestion that AD is a genuinely heterogeneous disease, has been proposed in the literature[28]. One paper[29] studies a 4-year longitudinal dataset, and identifies four different subgroups of AD patients which differ by the rate of their intellectual and functional decline as well as other symptoms. Ref.[30] states that AD shows heterogeneity in its clinical, anatomic, and physiologic characteristics, and identifies several patient subtypes with respect to different characteristics, including the time course of progression. In particular, inhomogeneity is observed with respect to the rates of ventricle enlargement, which are related to rates of cognitive decline. In Ref.[31], the presence of aphasia in AD patients is correlated with a more rapid course of the disease. This is done by performing extensive testing of the patients, as well as interviewing reliable informants, in the course of a 2. 5 year-long follow-up. Ref.[2] follows patients for 3 year, and discovers an association between relatively severe frontal lobe involvement and a rapid clinical course of AD, measured by using the dementia rating scale and estimating the symptom duration time. A recent paper, Ref.[32], examines AD data from a 15-year longitudinal study, and provides important insights into the patterns of progression of AD. It identifies three groups of patients based on their initial( pre-progression) rate. This rate is estimated by using the( normalized) Mini Mental Status Exam( MMSE) score at base-line, divided by the symptoms' duration. It is found that the different groups remain separate in the course of the follow-ups, which is consistent with our previous finding[33]. Most relevant to our present study, it is found that the average rates of decline for the three groups are different for three types of measures: a cognitive measure( Alzheimer's disease Assessment Scale-Cognitive Subscale), a functional measure( Physical Self-Maintenance Scale), and a global measure( Clinical Dementia Rating Scale Sum of Boxes). Although no direct estimate of the variation has been presented, these results clearly show that AD progression rates are heterogeneous in many respects. The patient data used here come from a longitudinal study conveyed between 1983 and 2006. It is theoretically possible that the large variation observed in the cohort of patients is a consequence of a change in lifestyle factors, which affected the course of AD progression. To explore this possibility, we have split the cohort of patients into two subgroups based on their dates of visit, and calculated the statistics of stage durations both for the “earlier” and the “later” parts of the cohort. We found that within the subgroups, the variances of the stage durations were as large as the ones reported here, and further, the mean values of stage durations were not significantly different. Note, however, that the analysis performed here was not specifically designed to discern slight trends in the disease progression over the decades. We cannot perform such an analysis with the data at hand because of the data scarcity issues( using smaller sub-groups of patients necessarily jeopardizes the reliability of the statistics). More data would be needed to catch the trends related to changes in life-style and other generational effects. Here we could only conclude that in both early and late halves of the cohort, the variances were large, and stage durations were statistically not different. Given a high variability of progression patterns, an important question is finding variables that correlate with progression rates. We have attempted to relate the rate of progression to demographic factors, and determine if it correlates with age at baseline, sex, education, or the age of onset of AD( which was back-calculated by using the information on the estimated stage durations). No significant correlations with these factors have been found, which is consistent with several previous papers[2],[13]–[19]. In the literature, several factors have been proposed to be predictive of the disease progression rate. The work of[34] highlights the heterogeneity of AD, and shows that clusters of CSF biomarker levels are related to patients' cognitive profiles. In particular, it finds that patients with extremely high CSF levels of tau and tau phosphorylated at threonine 181 demonstrate a distinct cognitive profile with more severe impairment of memory, mental speed, and executive functions; importantly, these differences cannot be explained by disease severity. Paper[35] finds that at the time of diagnosis, a combination of high CSF tau without proportionally elevated p-tau-181 is correlated with a faster rate of cognitive decline in AD patients. In paper[36], the variability of AD is explained in terms of specific types of EEG abnormalities. In paper[37], heterogeneity of AD is related to genetic variation in patients, such as that associated with cerebrospinal fluid phospho-tau levels. It is plausible that a combination of many different factors is responsible for a high variability of AD progression rates. Our main finding is the large heterogeneity in the duration of GDS/FAST stages in AD, which is consistent with the reports cited above. Our methods however are very different. In this study we use a very extensive( 23-year long) longitudinal dataset for AD patients, where there is a representation of patients at GDS/FAST stages 4–7 of AD. We calculate the amount of variance in patients explicitly, and demonstrate a large spread in values of GDS/FAST stage values for stages 4, 5, and 6. There are several applications of our results. To conclude, we analyzed a longitudinal dataset to extract the mean and the standard deviation for GDS/FAST stage durations for stages 4–6 of AD. Applying similar methodology to larger datasets with more frequent assessments will reveal more accurate results.
In recent decades , our understanding of Alzheimer's disease ( AD ) has increased; however , some basic questions still remain unresolved . One of them is: how homogeneous is AD ? Is the course of progression more or less the same for most patients , or are there large variations ? Our paper studies a large cohort of AD patients which comes from a 23-year-long study , and performs a statistical analysis of progression speed . We quantify the amount of spread in GDS/FAST stage durations ( a staging system widely used by clinicians ) . We arrive at an astonishing conclusion that the mean length of AD stages is comparable with their standard deviation ! This means that individual courses of AD progression may differ very much from each other , and from the textbook mean values . This has implications both for clinical trials ( how do we assess if a new drug is effective , if the amount of natural spread is so large in untreated patients ? ) , and for our understanding of this disease , which appears to be comprised of sub-diseases with different patterns of decline .