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Original Investigation |

The Growth and Impact of Alzheimer Disease Centers as Measured by Social Network Analysis

Michael E. Hughes, PhD1,2; John Peeler, BA1; John B. Hogenesch, PhD1,3; John Q. Trojanowski, MD, PhD4,5
[+] Author Affiliations
1Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia
2Department of Biology, University of Missouri–St Louis
3Department of Pharmacology, University of Pennsylvania School of Medicine, Philadelphia
4Center for Neurodegenerative Disease Research, Philadelphia, Pennsylvania
5Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania School of Medicine, Philadelphia
JAMA Neurol. 2014;71(4):412-420. doi:10.1001/jamaneurol.2013.6225.
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Importance  Alzheimer disease (AD) is a neurodegenerative disorder with no effective therapies. In 1984, the National Institute on Aging created the first 5 AD centers (ADCs) in an effort to coordinate research efforts into the pathology and treatment of the disease. Since that time, the ADC program has expanded to include 27 centers in major medical schools throughout the United States. A major aim of ADCs is to develop shared resources, such as tissue samples and patient populations, and thereby promote large-scale, high-impact studies that go beyond the capabilities of any single investigator or institution working in isolation.

Objective  To quantitatively evaluate the performance of the ADC program over the past 25 years.

Design and Setting  We systematically harvested every article published by ADC investigators and used social network analysis to analyze copublication networks.

Results  A total of 12170 ADC papers were published from 1985 through 2012. The frequency of collaborations has increased greatly from the time that the ADCs were started until the present, even after the expansion of ADCs and the recruitment of new investigators plateaued. Moreover, the collaborations established within the context of the ADC program are increasingly interinstitutional, consistent with the overall goal of the program to catalyze multicenter research teams. Most important, we determined that collaborative multi-ADC research articles are consistently of higher impact than AD articles as a whole.

Conclusions and Relevance  The ADC program has successfully fostered high-impact, multiuniversity collaborations; we suggest that its structural and administrative features could be replicated in other fields of patient-oriented research.

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Figure 1.
Copublication Networks of Alzheimer Disease Center (ADC) Investigators, 1985-2012

Publications from active ADC investigators were harvested from public databases, and networks of coauthorship were generated for every year from 1985 to 2012. Each red circle (ie, each node) represents a single active ADC investigator. Each blue line linking 2 nodes (ie, each edge) represents shared coauthorship of an article between 2 investigators. Blue edges with increased width represent coauthorship of more than 1 publication. Representative networks are shown for 1985 (A); 1990 (B); 1995 (C); 2000 (D); 2005 (E); and 2010 (F). These networks illustrate the growth of ADCs over the past 25 years in terms of the number of active investigators as well as the collaborative interactions among them.

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Figure 2.
Network Statistics for Collaborative Alzheimer Disease Center (ADC) Publications

Descriptive statistics were calculated from the copublication networks shown in Figure 1. A, Total number of unique ADC publications on a year-by-year basis, with data fit to a linear regression line. B, Total number of linked ADC investigators within each network, that is, active ADC investigators who published an article with another ADC investigator per year. These data were fit to a second-order polynomial. C, Number of links between ADC investigators per year. Columns in blue represent intra-ADC collaborations, that is, copublication links between 2 investigators within the same ADC. Columns in light blue represent inter-ADC collaborations, that is, copublication between 2 investigators in different ADCs. These data were fit to a linear regression line. D, Percentage of edges that came from inter-ADC collaborations. These data were fit to a second-order polynomial. E, The main cluster size of copublication networks, that is, the percentage of nodes connected by 1 or more edges to the largest subnetwork. These data were fit to a second-order polynomial. F, The number of edges per node for copublication networks. The growth of interconnectivity between ADC investigators is shown by the positive trend in node degree over time (NDT = 0.274). The inset bar graph shows that most of this increase in node degree originated from the increasing frequency of inter-ADC collaborations.

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Figure 3.
Interaction Networks Between Different Alzheimer Disease Centers (ADCs)

A, The geographic distribution of active ADCs and the collaborative links between them. Each red circle represents a single ADC, and each blue line represents collaborative publications shared between 2 ADCs. The width of each blue line is proportional to the number of copublications shared between 2 centers. This network represents every collaborative link established during the lifetime of the ADCs (1985-2012) rather than the year-by-year networks shown in Figure 1. B, The number of unique connections to other ADCs for each center (mean, 29.6). C, The number of total connections between ADCs, that is, the total number of collaborative articles spanning different ADCs (mean, 122.5). These data indicate that most active ADCs have established direct collaborative interactions with most other ADCs. MGH indicates Massachusetts General Hospital; NYU, New York University; UC, University of California; UCLA, University of California, Los Angeles; UCSD, University of California, San Diego; UCSF, University of California, San Francisco; USC, University of Southern California; UTSW, The University of Texas Southwestern.

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Figure 4.
Evolution of the Interests and Methodologies of Alzheimer Disease Centers (ADCs)

Medical Subject Headings (MeSH) terms were harvested from public databases for every ADC article. The MeSH terms that were used at least once per year, on average, were selected for further analysis (n = 700). A, The rate of change in MeSH term use as measured by the slope of a linear regression line during the lifetime of ADCs for all 700 MeSH terms. Most of these terms showed constant use in the ADC literature, with slopes near zero. Broken lines represent 2 SDs plus and minus the mean value of these data. At both extremes, the frequency substantially changed for several dozen MeSH terms. B, The increased frequency of publications dealing with the human genetics of AD, including the terms AD genetics, single-nucleotide polymorphisms (SNPs), and geneticpredisposition to disease, is evident. C, The shift in model systems from predominantly rats to transgenic mice is shown. D, An increased awareness of the influence of a patient’s sex on AD is illustrated. E, The growing focus on how a patient’s age affects the diagnosis and progression of AD is shown.

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Figure 5.
Scientific Impact of Multicenter Alzheimer Disease Center (ADC) Publications

The total number of citations received for inter-ADC collaborative publications were harvested from public databases. These citation counts were compared with the number of citations received for every publication of the topic of AD since 1985. For the purpose of this analysis, only primary research articles were considered. A, The number of citations received per article as a function of time. The blue lines represent the percentiles of citations received for the AD field as a whole. Each red circle represents the citations received by a single multicenter ADC publication. B, The percentages of collaborative multicenter ADC publications and of all randomly sampled ADC publications reaching the 99th, 90th, 75th, or 50th percentile of citations received in any given year. Collaborative ADC publications have shown typically higher impact than the AD field as a whole.

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