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6 Analysis of Institute and Center Autoimmune Disease Research Activity Both extramural and intramural autoimmune disease research occurs across the various Institutes, Centers, and Offices at the National Insti- tutes of Health (NIH), including the Office of the Director (OD). As noted in Chapter 5, total spending for autoimmune research was $1,083,000,000 for fiscal year (FY) 2020 (NIH, 2020a), a 2.6 percent increase from FY 2019. NIHâs investment in autoimmune disease research has remained constant at about 2.8 percent of its total obligations between 2008 and 2020 (Figure 6-1).1,2 From 2015 to 2020, total NIH obligations increased by 40 percent, whereas autoimmune disease spending increased by approximately 34 percent. Over the 2008â2020 period, NIH-funded autoimmune disease research activities totaled approximately $11.7 billion. The highest levels of spending on autoimmune disease occurred in 2009 and more recently in 2020 (Figure 6-2). As noted in Chapter 5, some Institutes and Centers (ICs) have a greater focus on autoimmune diseases tied to their mission, and thus there is considerable variation in the level of spending on autoimmune disease research activities. The OD also contributes funds to support autoimmune research activities. Table 6-13 shows total Institute, Center, and OD obliga- tions, autoimmune disease spending, autoimmune spending as a percent- age of total obligations, and average spending over the 2008â2020 period. 1 All NIH RePORTER data used in this report was accessed on July 16, 2021. 2 See Appendix G for methodology. 3 See Appendix G for methodology. 345 PREPUBLICATION COPYâUncorrected Proofs
346 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-1â NIH Actual total obligations and autoimmune disease spending, FY 2008â2020. SOURCES: NIH, 2020a, 2021b.
FIGURE 6-2â NIH Autoimmune disease spending, FY 2008â2020. PREPUBLICATION COPYâUncorrected Proofs NOTE: FY, Fiscal Year. SOURCE: NIH, 2020a. 347
348 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-1â IC FY 2020 Actual Total Obligations, Autoimmune Disease Spending, and Average Autoimmune Disease Spending for FY 2008â2020 FY 2020 Average Autoim- FY 2020 Autoim- Percent mune Disease Insti- FY 2020 Actual mune Disease Autoimmune Spending, tute Total Obligations Spending Spending FY 2008â2020 NCI $6,418,988,000 $35,369,000 0.5 $24,973,000 NIAID $5,880,084,000 $278,303,000 4.7 $209,707,000 NHLBI $3,624,863,000 $76,372,000 2.1 $65,729,000 NIGMS $2,937,142,000 $15,653,000 0.5 $13,682,000 NINDS $2,443,099,000 $79,386,000 2.2 $75,439,000 NIDDK $2,220,977,000 $347,207,000 15.6 $282,810,000 NICHD $1,556,841,000 $10,516,000 0.7 $15,975,000 NIEHS $883,808,000 $12,023,000 1.4 $13,619,600 NCATS $832,856,000 $8,757,000 1.0 $3,259,000 NEI $823,310,000 $33,983,000 4.1 $26,219,000 NIAMS $624,832,000 $147,716,000 23.6 $130,857,000 NHGRI $604,083,000 $10,469,000 1.7 $10,434,000 NIDCR $477,644,000 $18,880,000 3.9 $16,727,000 OD $1,467,130,000 $14,910,000 3.1 $21,649,000 NOTES: ICs are arranged in descending order according to FY 2020 actual total obligations. The Office of the Director (OD) is not an Institute but is included because of its funding contributions to autoimmune disease research. FY, Fiscal Year; IC, Institutes and Centers; NCATS, National Center for Advancing Translational Sciences; NCI, National Cancer In- stitute; NEI, National Eye Institute; NHGRI, National Human Genome Research Institute; NHLBI, National Heart, Lung, and Blood Institute; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIDCR, National Institute of Dental and Craniofacial Research; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIEHS, National Institute of Environmental Health Sciences; NIGMS, National Institute of General Medical Sciences; NINDS, National Institute on Neurological Disorders and Stroke; OD, Office of the Director. SOURCES: NIH, 2021b, 2021f. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 349 In 2020, the ICs with the highest level of spending on autoimmune disease research were the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), and National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). NIAMS autoimmune disease spending as a percentage of actual total obligations was the highest at 23.6 percent, fol- lowed by NIDDK (15.6 percent). Although NIAID had the third highest level of autoimmune disease spending, it was only about 5 percent of its total obligations in FY 2020. These three Institutes also had the highest average spending on autoimmune disease research during the 2008â2020 period. In 2020, of the total $1,125,730,564 spent on autoimmune disease research, NIDDK (30.8 percent), NIAID (24.7 percent) and NIAMS (13.1) spending accounted for almost 70 percent of the total autoimmune disease spending (Table 6-2).4 CHARACTERISTICS OF RESEARCH ACTIVITIES SUPPORTED BY ICS NIH uses 245 activity codes to characterize the funding mechanisms it employs to fund diverse activities. The committee focused on a select number of activity codes to characterize NIH- and IC-funded autoim- mune disease research activities. The committee used RePORTER activity code data to assess autoimmune disease research activities by extramural research (R and P grants); cooperative agreements (U grants); and fel- lowship, training and training center activities (F, K, and T grants); and intramural research activities (Z grants) (Table 6-3). Figure 6-3 provides NIH autoimmune disease funding for R, U, and P grants for FY 2008â2020 and the average funding for these grants over that period. Research project (R) grant funding for autoimmune disease research was highest in 2020 and lowest in 2008 and during 2013-2016. Funding for cooperative agreements (U) grants was greater than funding for research program project and center grants (P) during FY 2008â2020. Funding for cooperative agreements increased from 2008 to 2017, dropped in 2018, and began to rise again in 2019 and 2020. Funding for research programs project and centers was slightly higher in 2009â2011 and remained con- stant after 2011. Training grants contribute to building the autoimmune disease research workforce and to advancing research in the area. Table 6-45 shows NIH funding for fellowships (F), research career programs (K), and institutional training programs (T). Research career program grants had higher levels of funding throughout the entire period. 4 See Appendix G for methodology. 5 See Appendix G for methodology. PREPUBLICATION COPYâUncorrected Proofs
350 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-2â IC FY 2020 Autoimmune Disease Spending and Percent of Total NIH 2020 Autoimmune Disease Spending IC FY 2020 Percent of Total NCI $35,369,000 3.1% NIAID $278,303,000 24.7% NHLBI $76,372,000 6.8% NIGMS $15,653,000 1.4% NINDS $79,386,000 7.1% NIDDK $347,207,000 30.8% NICHD $10,516,000 0.9% NIEHS $12,023,000 1.1% NCATS $8,757,000 0.8% NEI $33,983,000 3.0% NIAMS $147,716,000 13.1% NHGRI $10,469,000 0.9% NIDCR $18,880,000 1.7% OD $14,910,000 1.3% All Other ICs $36,186,000 3.2% Total $1,125,731,000 100.0% NOTES: ICs are arranged in descending order according to FY 2020 actual total obligations. The Office of the Director (OD) is not an Institute but is included because of its funding contributions to autoimmune disease research. FY, Fiscal Year; IC, Institutes and Centers; NCATS, National Center for Advancing Translational Sciences; NCI, National Cancer In- stitute; NEI, National Eye Institute; NHGRI, National Human Genome Research Institute; NHLBI, National Heart, Lung, and Blood Institute; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIDCR, National Institute of Dental and Craniofacial Research; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIEHS, National Institute of Environmental Health Sciences; NIGMS, National Institute of General Medical Sciences; NINDS, National Institute on Neurological Disorders and Stroke; OD, Office of the Director. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 351 TABLE 6-3â Committee-Reviewed NIH Grant Types, by Activity Code NIH Grant Types Activity Purpose Code Extramural Research Research project grants may be awarded for discreet, specific research projects to individuals at universities, medical and other health professional schools, colleges, R Research Projects hospitals, research institutes, for- profit organizations, and govern- ment institutions. Typically, these grants are awarded for three to five years. The most common R award is the R01. Program project/center grants are large, multidisciplinary, and long- Research Program Projects and P term research efforts that generally Centers include a diverse array of research activities. Cooperative Agreements Cooperative agreements are a sup- port mechanism frequently used for complex, high-priority research U Cooperative Agreements areas that require substantial involvement from NIH program or scientific staff. Fellowships, Training, Training Centers Fellowships provide individual research training opportunities F Fellowship Programs (including international) for trainees at the undergraduate, graduate, and postdoctoral levels. Research Career Development awards provide individual and Research Career Development institutional research training op- K Programs portunities (including international) to trainees at the undergraduate, graduate, and postdoctoral levels. PREPUBLICATION COPYâUncorrected Proofs
352 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-3â Continued Institutional Training awards enable institutions to provide individual research training opportunities T Institutional Training Programs (including international) for trainees at the undergraduate, graduate, and postdoctoral levels. Intramural Research Z grants support research activities Z Intramural research of NIH intramural researchers. SOURCES: NIH, 2019; NIH Grants & Funding, 2021. The committee examined the proportion of Autoimmune Disease spending used for training to total Autoimmune Disease spending and compared it to other RCDC spending categories (Table 6-5). The compari- son groups are chronic diseases and are more common in women or have a similar prevalence between men and women (cardiovascular). IC FUNDING OF GRANTS To explore ICâs use of grants to further autoimmune disease research, the committee examined IC funding for research (R), cooperative agree- ment (U), and training grants (F, K, T). Figure 6-4 and Figure 6-5 present funding of research grants (R) categorized by ICs with the largest research budgets and smaller research budgets. For the purposes of this report, ICs are arranged in order by budget level and have been separated into two categories: large ICs and small ICs. Large ICs have FY 2020 actual total obligations greater than $1 billion and small institutes have actual total obligations of less than $1 billion. Among the larger ICs, NIDDK and NIAID had the highest level of fund- ing for research grants (R) in FY 2020. NIDDK had the highest level of average autoimmune disease research funding compared with the other ICs. Among the smaller ICs, NIAMS had a significantly higher level of funding in 2020 and average of funding for 2008â2020 for grants to sup- port autoimmune disease research (R) compared to other small ICs. The OD spent an average of $10 million on autoimmune research grants, which was comparable to the average funding spent by other smaller ICs. Cooperative agreement (U) grants support research activities that NIH considers to be complex and of high-priority research areas. Unlike independent investigator research (R) grants, cooperative agreements require greater involvement from NIH program or scientific staff. Figures 6-6 and 6-7 show the level of funding for autoimmune disease cooperative agreement grants for large and small ICs. PREPUBLICATION COPYâUncorrected Proofs
FIGURE 6-3â NIH autoimmune disease funding by research (R), cooperative agreement (U), and research Program project and center (P) grants, FY 2008â2020 (in millions). PREPUBLICATION COPYâUncorrected Proofs NOTE: FY, Fiscal Year. SOURCE: NIH, 2021f. 353
354 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-4â Autoimmune Disease Spending: Fellowship, Research Career, and Training Program Grant Funding per FY 2008â2020 and Average over the Period FY Fellowship Research Career Training Program 2008 $2,877,000 $26,431,000 $5,121,000 2009 $3,636,000 $28,202,000 $4,778,000 2010 $4,216,000 $26,562,000 $5,242,000 2011 $3,880,000 $27,727,000 $4,981,000 2012 $3,383,000 $28,948,000 $4,357,000 2013 $3,634,000 $29,209,000 $4,749,000 2014 $3,839,000 $28,621,000 $4,911,000 2015 $3,935,000 $27,736,000 $4,388,000 2016 $4,215,000 $28,814,000 $5,353,000 2017 $4,130,000 $28,133,000 $5,756,000 2018 $4,504,000 $27,625,000 $5,502,000 2019 $4,582,000 $29,746,000 $5,025,000 2020 $5,288,000 $33,571,000 $4,786,000 Average $4,009,000 $28,564,000 $4,996,000 FY 2008â2020 NOTE: NIH Autoimmune Disease Activity Codes for fellowship (F), research career (K), and training program (T) grants. FY, Fiscal Year. SOURCE: NIH, 2021f. TABLE 6-5â Training Investment for Selected RCDC Spending Categories, FY 2020 RCDC Spending Fellow- Category ship Research Career Training FY 2020 Total Alzheimerâs 10.9% 72.5% 16.5% $47,440,000 Autoimmune Disease 12.1% 76.9% 11.0% $43,646,000 Breast Cancer 0.8% 2.2% 0.0% $717,665,000 Cardiovascular 9.4% 64.3% 26.3% $144,080,000 COPD 12.2% 87.8% 0.0% $7,531,000 NOTE: COPD, Chronic Obstructive Pulmonary Disease; FY, Fiscal Year; RCDC, Research, Condition, and Disease Categorization. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 355 Among the larger ICs (Figure 6-6), NIDDK had a significantly higher level of funding for cooperative agreement grants for autoimmune dis- ease research activities in FY 2020 and over the FY 2008â2020 period. NIDDK funding levels for U grants over the period and in FY 2020 were more than double that of NIAID, the IC with the next level of coopera- tive agreement funding. Other large Institute funding of U grants was less than $6 million in 2020. In FY 2020, NIAMS, among the smaller ICs (Figure 6-7) had the highest level of funding for cooperative agreements ($9 million). During the FY 2008â2020 period, NHGRI had the highest average U grant funding level ($7 million). Program project/center (P) grants support large, multidisciplinary, and long-term research on autoimmune disease. Figure 6-8 shows P grant funding levels of at least $1 million by IC. NIAID and NIAMS had the highest funding levels for P grants and were similar, although NIAID has a larger overall research budget than NIAMS. Institutes can play an important role in supporting the research work- force in their area of focus. Funding can help build the research workforce through fellowships (F), research career programs (K), and institutional training programs (T) grants, in addition to traditional research grants. Table 6-6 shows IC funding of training grants that support the auto- immune disease research workforce. In FY 2020, NIDDK, NIAID, and NHLBI had the highest level of funding for fellowship (F) grants ($2.0 million, $814,000, and $804,000 respectively). NIDDK also had the high- est average funding of fellowship grants over the FY 2008â2020 period ($1.6 million). ICs preferred funding mechanism for research career program (K) grants was the training grant mechanism. Funding for these grants was higher than funding for fellowships or institutional training programs grants. In FY 2020, NIDDK had the highest level of funding of K grants ($11.3 million), followed by NIAMS ($8.2 million). Over the FY 2008â2020 period, NIDDK ($9.8 million) and NIAMS ($7.9 million) had the highest level of average funding for K grants compared to other ICs. The commit- tee notes that OD funding for K grants was $1.1 million in FY 2020, which is more than double than the average funding over the FY 2008â2020 period. ICs other than NIAMS relied less on the T grant mechanism to sup- port training of autoimmune disease researchers. In FY 2020, NIAMS funded $3.9 million in T grants with an average funding level of $4.2 million over the FY 2008â2020 period. NIAID, NIDDK, and OD used this mechanism at a significantly lower funding level. PREPUBLICATION COPYâUncorrected Proofs
356 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-6â Training Grant Funding for Autoimmune Disease Research by Institute and Year Training as a Percent of FY 2020 Obliga- Institute Year(s) F K T tions FY 2020 $171,195 $584,384 $0 NCI 0.01% Average FY 2008â2020 $100,885 $349,586 $0 FY 2020 $814,263 $2,085,385 $653,017 NIAID 0.06% Average FY 2008â2020 $492,310 $2,454,588 $561,823 FY 2020 $804,583 $4,432,189 $0 NHLBI 0.14% Average FY 2008â2020 $442,446 $2,737,751 $0 FY 2020 $79,212 $198,504 $0 NIGMS 0.01% Average FY 2008â2020 $135,591 $118,849 $0 FY 2020 $432,647 $3,359,470 $0 NINDS 0.16% Average FY 2008â2020 $586,329 $2,324,825 $0 FY 2020 $2,062,032 $11,311,126 $93,836 NIDDK 0.61% Average FY 2008â2020 $1,640,982 $9,848,175 $159,663 FY 2020 $82,851 $570,283 $0 NICHD 0.04% Average FY 2008â2020 $26,922 $553,745 $0 FY 2020 $36,611 $87,463 $0 NIEHS 0.01% Average FY 2008â2020 $67,663 $65,037 $0 FY 2020 $0 $0 $0 NCATS - Average FY 2008â2020 $0 $0 $0 FY 2020 $0 $916,394 $0 NEI 0.11% Average FY 2008â2020 $14,717 $828,068 $0 FY 2020 $281,015 $8,247,061 $3,953,872 NIAMS 2.00% Average FY 2008â2020 $229,852 $7,926,922 $4,261,852 FY 2020 $64,926 $0 $0 NHGRI 0.01% Average FY 2008â2020 $4,994 $62,014 $0 FY 2020 $107,672 $0 $0 NIDCR 0.02%Â Average FY 2008â2020 $65,626 $139,637 $0 FY 2020 $0 $1,175,676 $85,655 OD 0.09% Average FY 2008â2020 $9,502 $491,711 $12,694 continued PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 357 TABLE 6-6âContinued NOTE: FY, Fiscal Year; IC, Institutes and Centers; NCATS, National Center for Advancing Translational Sciences; NCI, National Cancer Institute; NEI, National Eye Institute; NHGRI, National Human Genome Research Institute; NHLBI, National Heart, Lung, and Blood Institute; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIDCR, National Institute of Dental and Craniofacial Research; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIEHS, National Institute of Environmental Health Sciences; NIGMS, National Institute of General Medical Sciences; NINDS, National Institute on Neurological Disorders and Stroke; OD, Office of the Director. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
358 FIGURE 6-4 ICâ funding for research grants (R) by large ICs for FY 2020 and average FY 2008â2020 (in millions). NOTES: Large Institutes have FY 2020 actual total obligations greater than $1 billion. FY, Fiscal Year; IC, Institutes and Centers; NI- AID, National Institute of Allergy and Infectious Diseases; NCI, National Cancer Institute; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; PREPUBLICATION COPYâUncorrected Proofs NIGMS, National Institute of General Medical Sciences; NHLBI, National Heart, Lung, and Blood Institute; NINDS, National In- stitute of Neurological Disorders and Stroke. SOURCE: NIH, 2021f.
FIGURE 6-5â IC funding for research grants (R) by small ICs for FY 2020 and average FY 2008â2020 (in millions). NOTES: Small Institutes have FY 2020 actual total obligations less than $1 billion. While the Office of the Director (OD) is not an Institute, it is included in the small Institute category. National Human Genome Research Institute (NHGRI) did not fund R grants in 2020 but contributed an average of $704,274 per year over the 2008â2020 period for autoimmune disease research. National Center for Advancing Translational Sciences (NCATS) was not included in the figure because it became an Institute in 2012; In FY PREPUBLICATION COPYâUncorrected Proofs 2020, NCATS spent $226,174 on autoimmune disease research grants and an average of $493,918 per year over the FY 2008â2020 period. FY, Fiscal Year; IC, Institutes and Centers; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NIEHS, National Institute of Environmental Health Sciences; NEI, National Eye Institute; NIDCR, National Institute of Dental and Craniofacial Research. SOURCE: NIH, 2021f. 359
360 FIGURE 6-6â IC autoimmune disease funding for cooperative agreement (U) grants for large ICs, FY 2020 and average FY 2008â2020 (in millions). NOTES: Large Institutes have FY 2020 actual total obligations greater than $1 billion. FY, Fiscal Year; IC, Institutes and Centers; NIAID, National Institute of Allergy and Infectious Diseases; NCI, National Cancer Institute; NICHD, Eunice Kennedy Shriver PREPUBLICATION COPYâUncorrected Proofs National Institute of Child Health and Human Development; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIGMS, National Institute of General Medical Sciences; NHLBI, National Heart, Lung, and Blood Institute; NINDS, National Institute of Neurological Disorders and Stroke. SOURCE: NIH, 2021f.
FIGURE 6-7â IC autoimmune disease funding for cooperative agreement (U) grants for small ICs, FY 2020 and average FY 2008â 2020 (in millions). NOTES: Small Institutes have FY 2020 actual total obligations less than $1 billion. While the Office of the Director (OD) is not an Institute, it is included in the small Institute category. FY, Fiscal Year; IC, Institutes and Centers; NIAMS, National Institute of PREPUBLICATION COPYâUncorrected Proofs Arthritis and Musculoskeletal and Skin Diseases; NIEHS, National Institute of Environmental Health Sciences; NEI, National Eye Institute; NIDCR, National Institute of Dental and Craniofacial Research. SOURCE: NIH, 2021f. 361
362 FIGURE 6-8â IC autoimmune disease funding for program project/center (P) grants by ICs, FY 2020 and average FY 2008â2020 (in millions). NOTES: Institutes with Program/center (P) grant spending of less than $1 million in 2020 or over the 2008â2020 period are not shown in the graph, including National Eye Institute (NEI), National Institute of Environmental Health Sciences (NIEHS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Human Genome Research Insti- tute (NHGRI), National Institute of Dental and Craniofacial Research (NIDCR), and Office of the Director (OD). National Center for Advancing Translational Sciences (NCATS) did not have any P grant spending between 2012 and 2020. PREPUBLICATION COPYâUncorrected Proofs IC, Institutes and Centers; FY, Fiscal Year; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Disorders; NCI, National Cancer Institute; NHLBI, National Heart, Lung, and Blood Institute; NIGMS, National Institute of General Medical Sciences; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NINDS, National Institute of Neurological Disorders and Stroke. SOURCE: NIH, 2021f.
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 363 The committee reviewed NIH spending on autoimmune disease research by type of grant and type of research according to three catego- ries: intramural, investigator-initiated, and solicited. As noted earlier, intramural research funding (Z) is for internal NIH investigator research activities, and research (R) grant funding is the most common indepen- dent research grant mechanism. ICs use solicited research funding oppor- tunities to support priority research areas. NIH communicates with the research community about these grant opportunities through a notice of special interest, program announcement, request for application, request for proposal, and other mechanisms. Figure 6-96 shows NIH funding for autoimmune disease research for the average over the study period and FY 2020. Of the three types of grants, investigator-initiated research grants received more than 70 percent of the funding, however funding for each type of research in FY 2020 is higher than the average over the study period. Table 6-7 shows funding of intramural, investigator-initiated, and solicited grants by ICs. Funding for intramural research was highest for NIAID and NIAMS (about $34 million each) in FY 2020 (Table 6-7)7. NIAID and NIDDK had the highest level of funding for investigator-initiated research ($187 mil- lion and $185 million respectively), followed by NIAMS ($86 million). NIDDK had the highest level of average FY 2008â2020 funding ($127 million per year). Of the Institutes reviewed, NIDDK also had the highest level of funding for solicited research grants. NIDDK solicited research funding was 2.7 times higher than NIAID funding for this grant type. Intramural research activities represent 17.3 percent of NIH funding for autoimmune research in FY 2020.Â A total of 50 intramural principal investigators conduct autoimmune disease research, which may include basic, translational, and clinical studies.Â However, the committee notes that there is a relative lack of intramural principal investigators who focus on epidemiology and autoimmune diseases. The committee searched the NIH Intramural Research Program database8 to identify principal inves- tigators who conduct autoimmune research and principal investigators who engage in epidemiology-focused research (N=121).Â There are three intramural principal investigators who conduct research that overlaps both of these areas. This number is significantly lower than the number 6 See Appendix G for methodology. 7 See Appendix G for methodology. 8The committee used the NIH Intramural Research Program database available at https:// irp.nih.gov/our-research/principal-investigators/focus/epidemiology (accessed January 7, 2022). PREPUBLICATION COPYâUncorrected Proofs
364 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE FIGURE 6-9â NIH funding for autoimmune disease research for the average FY 2008â2020 and FY 2020. NOTES: Autoimmune disease research categories were determined using Funding Opportunity Announcement (FOA) and Combined Total Cost of Funded Autoim- mune Disease Research. Grants without an FOA were not included in the analysis. FY, Fiscal Year; IC, Institutes and Centers. SOURCE: NIH, 2021f. of principal investigators in the NCI intramural research program whose research focuses on both cancer and epidemiology (N=69). RESEARCH GRANTS BY AUTOIMMUNE DISEASE NIH introduced the Research, Condition, and Disease Categorization (RCDC) in 2009 to categorize funded research. RCDC categories include disease, condition, or disease area, but the categories are not exhaus- tive or mutually exclusive (NIH, 2021a). Funded research as reported in NIH RePORTER may have multiple RCDC disease spending categories depending on the scientific and research focus of the project. Further- more, diseases or conditions that do not have a specific RCDC spending category (diabetes mellitus type 1, antiphospholipid syndrome, SjÃ¶grenâs disease, celiac disease, autoimmune thyroid disease, primary biliary chol- angitis) must be searched for using âkey terms,â including the name of PREPUBLICATION COPYâUncorrected Proofs
TABLE 6-7â Intramural, Investigator-Initiated, and Solicited Autoimmune Disease Research by IC, FY 2020 and Average FY 2008â2020 Institute Intramural Investigator-Initiated Solicited Average Average Average FY 2020 FY FY 2020 FY FY 2020 FY Â 2008â2020 2008â2020 2008â2020 NCI $14,270,000 $10,882,000 $11,684,000 $10,347,000 $9,416,000 $2,074,000 NIAID $34,006,000 $21,769,000 $187,328,000 $107,751,000 $55,735,000 $42,976,000 NHLBI $11,701,000 $4,077,000 $59,078,000 $39,906,000 $5,593,000 $14,307,000 NIGMS $0 $0 $15,026,000 $10,947,000 $629,000 $1,744,000 NINDS $13,474,000 $9,765,000 $54,562,000 $50,127,000 $11,350,000 $3,113,000 NIDDK $7,566,000 $4,921,000 $185,951,000 $127,257,000 $153,690,000 $120,316,000 NICHD $1,964,000 $3,444,000 $7,844,000 $8,163,000 $709,000 $1,855,000 NIEHS $4,724,000 $7,439,000 $4,602,000 $4,202,000 $2,101,000 $1,170,000 NCATS $2,606,000 $1,564,000 $590,000 $472,000 $2,801,000 $2,801,000 NEI $14,983,000 $9,614,000 $18,624,000 $10,587,000 $376,000 $128,000 NIAMS $35,790,000 $28,182,000 $86,159,000 $72,297,000 $25,767,000 $20,573,000 NHGRI $7,003,000 $3,945,000 $65,000 $371,000 $3,401,000 $6,688,000 NIDCR $4,930,000 $7,740,000 $13,950,000 $6,191,000 $0 $1,350,000 PREPUBLICATION COPYâUncorrected Proofs OD $0 $0 $3,316,000 $4,668,000 $11,595,000 $15,929,000 365
366 the condition and all iterations of it (e.g., names roughly equivalent to antiphospholipid syndrome include Hughesâ syndrome, lupus anticoagu- lant, anticardiolipin, etc.). The committee was interested in examining trends in the number of grants for autoimmune diseases of specific interest identified in Chapter 3. These diseases include inflammatory bowel disease, multiple sclerosis, type 1 diabetes, rheumatoid arthritis, systemic lupus erythem- atous, SjÃ¶grenâs disease, psoriasis, celiac disease, autoimmune thyroid disease, antiphospholipid syndrome, and primary biliary cholangitis. Hashimotoâs disease and Graveâs disease were combined into a single âautoimmune thyroid diseaseâ category. In addition, grants that were not associated with the committeeâs specific disease categories or were not disease specific were labeled as âother autoimmune diseaseâ throughout the analysis. RePORTER data includes funding information for each year of a grant (for example a 3-year R01 grant is identified as three increments of funding); the committee aggregated funding increments with the same grant number to represent one grant. In total, the committee identified and aggregated 28,148 funding increments into 8,470 autoimmune disease grants.9 Figure 6-10 shows number of grants by disease category for FY 2008â2020. Of the autoimmune diseases the committee examined, the four dis- eases with the greatest number of funded grants over the FY 2008â2020 period were other autoimmune diseases (31.0 percent), inflammatory bowel disease (17.6 percent), multiple sclerosis (16.4 percent) and type 1 diabetes (13.2 percent). Figure 6-11 shows the total number of grants by disease category funded by year, between 2008 and 2020. The number of inflammatory bowel disease and type 1 diabetes grants increased gradu- ally over time; multiple sclerosis grants declined after 2009. The number of other specific disease grants fluctuated over the period. Autoimmune disease grants involved 98 distinct activity codes. Fig- ure 6-12 shows the top 10 activity codes. Among these, R01 (35.9 percent) and R21 (12.4 percent) accounted for the largest number of grants are. R01 grants are the standard investigator-initiated grants and R21 grants are research exploratory/developmental grants meant to encourage the development of new research activities in specific program areas. For R01 grants, other autoimmune disease (light purple) multiple scle- rosis (dark purple), and inflammatory bowel disease (yellow) were the most funded grants in FY 2020 (Figure 6-13). The number of grants increased for about half of the disease categories after 2016. Inflammatory bowel disease grants increased steadily over the period. SjÃ¶grenâs disease, psoriasis, celiac 9Aggregated grants also include subprojects added to a parent project. PREPUBLICATION COPYâUncorrected Proofs
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-10â Number of grants by disease category, FY 2008â2020 (N=8,470). NOTES: Percentages in the figure add up to be more than 100 percent because grants can be associated with more than one auto- immune disease. FY, Fiscal Year. 367 SOURCE: NIH, 2021f.
368 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-11â Number of autoimmune disease grants by disease, FY 2008â2020 (N=8,470). NOTES: Percentages in the figure add up to be more than 100 percent because grants can be associated with more than one auto- immune disease. FY, Fiscal Year. SOURCE: NIH, 2021f.
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 369 disease, autoimmune thyroid disease, antiphospholipid syndrome, and primary biliary cholangitis had fewer than 25 grants per year. Among R01 research grants, non-competing continuation research grants (R01-5) were the most funded (32.5 percent) followed by new R01-1 grants (22.3 percent). Figure 6-14 shows the number of non-competing R01 grants by disease and Figure 6-15 shows new R01 grants by disease for FY 2008â2020. Non-competing continuation grants for all disease cat- egories decreased in 2016 as a result of an administrative accounting change (Figure 6-15). There were no clear patterns in the trends in the number of new R01 grants funded by disease categories except for the increase in inflammatory bowel disease grants over the study period. The committee also examined the ICs designated as the funding IC for autoimmune disease grants (Figure 6-16). Among the top 10 funding ICs, NIDDK, NIAID, and NIAMS funded the largest number of grants. Figures 6-17 through 6-19 show trends in autoimmune diseases by the top three funding ICs (NIDDK, NIAID, and NIAMS). Figure 6-17 shows that among NIDDK funded grants, the disease categories with the great- est number of grants were inflammatory bowel disease (yellow), type 1 diabetes (black), and other autoimmune disease (light purple). Figure 6-18 FIGURE 6-12â Top 10 activity codes for autoimmune disease research. NOTE: R01 are the standard investigator-initiated grants, R21 or research explor- atory or developmental grants for new research activities in categorical program areas, R43 are small business innovation research grants, R03 are small research grants for studies in categorical program areas. ZIA are intramural grants, R56 grants for high-priority, short-term projects, F31 are fellowship grants, K08 are clinical investigator career development awards, K23 are mentored patient-ori- ented research career development grants, and F32 are postdoctoral individual national research service awards. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
370 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-13â Number of R01 grants by autoimmune disease, FY 2008â2020. NOTE: FY, Fiscal Year. SOURCE: NIH, 2021f.
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-14â Number of non-competing continuation R01 grants (n=2,751) by autoimmune disease, FY 2008â2020. NOTES: In FY 2014 and 2015, non-competing awards were issued as extension awards to support NIHâs transition to Payment Management System subaccounts. The decrease in non-competing continuation R01 grants in 2016 is related to this accounting change. FY, Fiscal Year. SOURCE: NIH, 2021f. 371
372 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE shows NIAID-funded grants by disease. The top three disease categories with the most grants were other autoimmune diseases (light purple), systemic lupus erythematosus (dark blue), and multiple sclerosis (dark purple). While NIAID-funded inflammatory bowel disease grants (yel- low) seemed to increase steadily since 2011, systemic lupus erythematosus and multiple sclerosis grants decreased in 2015 but have since increased. Figure 6-19 shows NIAMS funded grants by disease. The top three disease categories with the most grants are rheumatoid arthritis (orange), other autoimmune diseases (light purple), and systemic lupus erythematosus (dark blue). IC Collaboration on Research Funding Opportunities ICs can take steps among themselves to coordinate their research interests and to leverage their mutual expertise and resources.10 One mea- sure of collaboration is the degree to which ICs engage in joint funding of specific autoimmune diseases research activities. To assess the level of col- laboration among ICs, the committee examined co-funded autoimmune disease research grants for FY 2008â2020. To accomplish this, the com- mittee used NIH RePORTER data to identify administrative ICs funding autoimmune disease research grants and corresponding funding ICs that contributed to the total cost of grants during this period. All 14 ICs collaborated with other ICs11 to co-fund autoimmune research activities during the period. Among the large ICs, NIAID (4.23), NHLBI (2.70), and NIDDK (2.62) had the largest average number of joint IC funding collaborations (Table 6-8)12. These ICs jointly funded research grants with one to six other ICs in a given year and collaborated with eight to nine different ICs over the period. NIDDK collaborated con- sistently with at least one IC each year and with up to six ICs during a given year. Among the smaller ICs, NIAMS (3.4) had the highest average number of joint IC funding collaborations followed by NIDCR (1.10) and NCATS (1.00). NIAMS collaborated with nine different ICs over the period. NIDCR and NCATS collaborated with four and three different ICs (respectively) during the period. Most collaborations were on P, R, and U grants. 10 According to multiple NIH speakers who spoke at the committeeâs public information- gathering sessions (Goldmuntz, 2020; Hodge, 2021; McNamara, 2021). 11 ICs of the committeeâs focus. 12 See Appendix G for methodology. PREPUBLICATION COPYâUncorrected Proofs
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-15â New R01 grants by autoimmune disease (N=1,892), FY 2008â2020. NOTE: FY, Fiscal Year. SOURCE: NIH, 2021f. 373
374 FIGURE 6-16â Top 10 funding ICs by grants, FY 2008â2020 (N=8,470). NOTES: Percentages do not sum to 100 percent because the figure includes only the top 10 funding ICs and does not include grants without a funding IC listed in NIH RePORTER. FY, Fiscal Year; IC, Institutes and Centers. PREPUBLICATION COPYâUncorrected Proofs SOURCE: NIH, 2021f.
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-17â NIDDK (funding IC) grants by disease, FY 2008â2020. NOTES: This graph represents the number of grants with NIDDK funding. NIDDK was not necessarily the sole funder of each grant. FY, Fiscal Year; IC, Institutes and Centers. SOURCE: NIH, 2021f. 375
376 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-18â NIAID (funding IC) grants by disease, FY 2008â2020. NOTES: This graph represents the number of grants with NIAID funding. NIAID was not necessarily the sole funder of each grant. FY, Fiscal Year; IC, Institutes and Centers. SOURCE: NIH, 2021f.
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-19â NIAMS (funding IC) grants by disease, FY 2008â2020. NOTES: This graph represents the number of grants with NIAMS funding. NIAMS was not necessarily the sole funder of each grant. FY, Fiscal Year; IC, Institutes and Centers. SOURCE: NIH, 2021f. 377
378 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE RESEARCH FOCUS OF FUNDED GRANTS The statement of task directed the committee to evaluate the NIH research portfolio with particular attention to issues such as risk fac- tors, diagnostic tools, barriers to diagnoses, treatments, and prospects for cures. Given the enormity of the task, which would have required that the committee review the 8,470 abstracts associated with the autoimmune disease grants funded from 2008â2020, the committee found three ways to approach the task in a more efficient and manageable way. The first approach used research topic modeling, a type of statistical modeling to identify popular âtopicsâ that appeared in the abstracts. In the second approach, committee members utilized RCDC spending categories and RePORTER data to determine which particular spending categories were co-occurring with the autoimmune disease spending category. In the third approach, the committee reviewed a sample of research grant abstracts to identify the primary focus of the research. The committee, with the aid of a consultant, used latent dirichlet allocation (LDA) statistical modeling to identify research topics in the set of 8,470 NIH research abstracts related to autoimmune disease grants funded between 2008 and 2020. Topic modeling using LDA is a method of fitting a pre-determined number of topics to a set of texts. The LDA algo- rithm repeatedly selects and assigns words in each document to a topic and assesses the âfitâ of the word to the topic by looking at what words are frequently found together across the texts (Blei et al., 2003). In the past, researchers have applied LDA modeling to scientific abstracts to analyze funding patterns and trends in research (Park et al., 2016; Porturas and Taylor, 2021). Based on the coherence score of words13 that tended to co- occur together in the dataset, 30 topics were determined to be the optimal number of topics that could be used to fit the data (words) in the abstracts (Bittermann and Fischer, 2018; Park et al., 2016; Porturas and Taylor, 2021). See Appendix H for more detailed information. One of the outputs of the LDA model is a matrix that shows the pro- portion of topics assigned to each abstract. For example, 30 percent of the words in an abstract might belong to topic 1 and 70 percent of words in an abstract might belong to topic 2. The topic with the highest proportion within each abstract was assigned to the abstract. Topics were combined 13 Coherence score is a score that calculates if the words in the same topic make sense when they are grouped together and is an indicator of the quality of the topics being produced (Cristian, 2020). PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 379 TABLE 6-8â IC Collaboration, FY 2008â2020 Large ICs Average Number of Joint Range of Joint IC Number of IC Funding Collaboration Funding Collaboration Collaborating ICs IC (2008â2020) per Year (2008â2020) NCI 1.38 0-4 4 NIAID 4.23 3-6 8 NHLBI 2.70 1-5 9 NIGMS 1.77 0-4 5 NINDS 1.62 0-3 7 NIDDK 2.62 1-4 8 NICHD 2.00 1-3 5 Small ICs Average Number of Joint Range of Joint IC Fund- Number of Collabo- IC IC Funding Collaboration ing Collaboration per rating ICs (2008â2020) Year (2008â2020) NIEHS 0.54 0-1 1 NCATS 1.00 1-3 3 NEI 0.23 0-1 1 NIAMS 3.54 1-6 9 NHGRI 0.38 0-1 2 NIDCR 1.10 0-2 4 OD 0.46 0-1 2 NOTES: Large Institutes have FY 2020 actual total obligations greater than $1 billion and small institutes have actual total obligations of less than $1 billion. All ICs in this table are administrative ICs. FY, Fiscal Year; IC, Institutes and Centers; NCATS, National Center for Advancing Translational Sciences; NCI, National Cancer Institute; NEI, National Eye Insti- tute; NHGRI, National Human Genome Research Institute; NHLBI, National Heart, Lung, and Blood Institute; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NICHD, Eunice Ken- nedy Shriver National Institute of Child Health and Human Development; NIDCR, National Institute of Dental and Craniofacial Research; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIEHS, National Institute of Environmental Health Sci- ences; NIGMS, National Institute of General Medical Sciences; NINDS, National Institute on Neurological Disorders and Stroke; OD, Office of the Director. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
380 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE BOX 6-1 LDA-Derived Topics Based on 8,470 Autoimmune Disease Grants Disease Focused Immune Clinical Topics Administrative Topics Response Topics Related Topics Psoriasis Immune response Treatment/ Centers/Core Lung Disease (innate immunity) Therapy Projects Funding Type 1 Diabetes Other (non- Disease Training (funding) SLE antibody) progression Cancer mechanisms Diagnostic Rheumatoid of adaptive Imaging Arthritis immunity Cardiovascular Animal model IBD Gene expression Multiple Sclerosis Epithelial Barrier Genetics Pathogenesis Virus (infectious etiology) NOTE: SLE, systemic lupus erythematosus; IBD, inflammatory bowel disease based on similarity of words within topics. Box 6-1 shows the final list of 23 topics that fit the data the best. Figures 6-20 through 6-23 show the frequency of these topic assign- ments from 2008â2020. This graphic is a depiction of the popularity of the research topics in the grants over the period. Trends over time show that the research topics related to inflammatory bowel disease (IBD), treatment/therapy, lung disease, diagnostic [tools], and imaging have trended upward in contrast to animal model, genetics, and pathogenesis. Compared to the other disease focused topics, type 1 diabetes was preva- lent among grants over time (Figure 6-20). Cancer, rheumatoid arthri- tis, cardiovascular, and multiple sclerosis remained consistent over the time period. In Figure 6-21, immune response (innate immunity) may be disproportionately high because of its relevance to various aspects of autoimmune disease research as well as a lack of a concrete definition for innate immunity. Between 2008 and 2018, the mention of treatment/ therapy in autoimmune disease abstracts drastically increased, but then decreased sharply (Figure 6-22). However, mention of disease progres- sion, diagnostic, and imaging generally increased during the latter part of the decade. In Figure 6-23, centers/core project funding was variable PREPUBLICATION COPYâUncorrected Proofs
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-20â LDA-generated topics for NIH autoimmune disease grants, FY 2008â2020: Disease focused topics. NOTE: SLE, systemic lupus erythematosus; IBD, inflammatory bowel disease. SOURCE: NIH, 2021f. 381
382 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE throughout the time period, and there has been a consistent decrease in the mention of training being present in autoimmune disease abstracts, especially between 2015 and 2020. One of the downsides of using LDA for topic modeling is that the top- ics must be discovered âlatentlyâ within the texts and cannot be inputted into the model algorithm. In other words, this method cannot be used to actively search for specific research topics. RCDC Spending Categories The second approach the committee used to evaluate the NIH research portfolio was to determine which other NIH RCDC spending categories co-occur with the autoimmune disease spending category. This can pro- vide insight into themes within autoimmune disease research. The defi- nitions of the categories include all aspects of the topic, including basic, pre-clinical, clinical, biomedical, health services, behavioral, and social research, as defined by NIH scientific experts (NIH, 2020a). However, the definitions are not publicized. Table 6-9 shows the RCDC spending cat- egories that the committee selected for analysis based on the statement of task, concepts or conditions known to be related to autoimmune disease, and affected populations. Out of the 25 RCDC spending categories the committee analyzed, Genetics (32.1 percent), Biotechnology (23.4 percent), Prevention (22.9 percent), Pediatric (15.9 percent), and Womenâs Health (12.9 percent) were the top five spending categories co-occurring with the autoimmune disease spending category in a total of 8,470 grants. PICO Portal PICO Portal is an online tool used to review and manually categorize scientific literature. Given the large variation in the number of grants per disease, the committee decided to take weighted samples of the selected diseases as follows: a 10 percent sample of diseases with greater than 1,000 grants (âother autoimmune disease,â IBD, multiple sclerosis, type 1 diabetes, rheumatoid arthritis, and SLE), a 50 percent sample of diseases between 100 and 999 grants (SjÃ¶grenâs, psoriasis, and celiac disease), and a 100 percent sample of diseases with fewer than 99 grants (autoimmune thyroid disease and PBC). This resulted in a total of 1,148 grants. Grants were then deduplicated (because a grant could have been assigned to more than one disease), resulting in a final total of 1,127 grants for the committee to manually categorize. 1,127 is approximately 13 percent of the total number of grants (N=8,470). Research characteristics were chosen to evaluate the portfolio and identify the focus of the research. These characteristics encompass various PREPUBLICATION COPYâUncorrected Proofs
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-21â LDA-generated topics for NIH autoimmune disease grants, FY 2008â2020: Immune response related topics. SOURCE: NIH, 2021f. 383
384 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE FIGURE 6-22â LDA-generated topics for NIH autoimmune disease grants, FY 2008â2020: Clinical topics. SOURCE: NIH, 2021f. FIGURE 6-23â LDA-generated topics for NIH autoimmune disease grants, FY 2008â2020: Administrative topics. SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 385 TABLE 6-9â Percent of Autoimmune Disease Grants Co-occurring with other RCDC Spending Categories (N=8,470) Co-Occurring with Autoimmune Disease RCDC Spending Category Spending Category Genetics 2,718 32.1% Biotechnology 1,978 23.4% Prevention 1,938 22.9% Pediatric 1,349 15.9% Womenâs Health 1,095 12.9% Infectious Disease 1,007 11.9% Aging 688 8.1% Cancer 660 7.8% Minority Health 590 7.0% Cardiovascular 490 5.8% Immunotherapy 388 4.6% Eye Disease and Disorders of Vision 327 3.9% Microbiome 298 3.5% Biomedical Imaging 176 2.1% Precision Medicine 157 1.9% Pain Research 143 1.7% Health Services 132 1.6% Estrogen 71 0.8% Chronic Pain 56 0.7% Acquired Cognitive Impairment 49 0.6% Depression 42 0.5% Cerebrovascular 41 0.5% Fibromyalgia 14 0.2% Burden of Illness 12 0.1% Caregiving Research 2 0.0% SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
386 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE concepts in the statement of task, co-morbid diseases or complications of autoimmune disease, and type and method of research. Examining more than one autoimmune disease aimed to capture grants exploring the co- occurrence of autoimmune diseases. Within PICO Portal, the committee used the tagging feature to categorize the abstracts with one or more of the following research characteristics: animal model, cancer, cardiovas- cular, depression, diagnostic, environment/infectious agents, epidemi- ology, genetics, nursing/behavioral health services, pathophysiology/ mechanisms, pediatrics, primary prevention, treatment/therapy, in vivo human study, in vivo animal study, in vitro study, and more than one autoimmune disease. The committee predefined specific definitions of the research characteristics in order to tag abstracts objectively. Figures 6-24 and 6-25 show the number and percent of abstracts tagged with the research characteristics. More than half (59.1 percent) of the 1,127 abstracts were tagged as having a focus on pathophysiology/ mechanisms, followed by genetics (25.3 percent), treatment/therapy (23.2 percent), and animal model (23.2 percent). âAnimal modelâ refers to the development of a new in vivo animal study for use to study autoimmune disease, whereas âin vivo animal studyâ refers to the use of an already existing animal model. Approximately 22 percent of the abstracts men- tioned or focused on more than one autoimmune disease. In addition, the committee tagged abstracts based on the type of study researchers intended to conduct with their grant funding (Figure 6-25). Almost half of the abstracts were identified as being an in vivo animal study (48.4 percent), followed by in vitro (40.8 percent), and in vivo human study (29.3 percent). It is important to note the discrepancy between the RCDC spending category âpreventionâ and âprimary preventionâ as a predefined research characteristic tag in PICO Portal. The committee defined primary preven- tion, found in 1.3 percent of abstracts, as âresearch that focuses on pre- venting an autoimmune disease from occurring in an individual,â and is only one of the three levels of prevention. In contrast, almost one-third of autoimmune disease grants included the RCDC prevention category, suggesting that RCDC may use a different definition that includes other levels of prevention. Alternatively, depression as both an RCDC category and a PICO Portal research characteristic tag both occurred infrequently in autoimmune disease grants (0.5 percent). This points to a potential opportunity to explore depression as a disease that coincides with auto- immune disease. PREPUBLICATION COPYâUncorrected Proofs
FIGURE 6-24â Research characteristics identified within autoimmune disease grant abstracts (N=1,127). NOTE: Percentages in the figure add up to be more than 100 percent because grants could be tagged with more than one research characteristic. PREPUBLICATION COPYâUncorrected Proofs SOURCE: NIH, 2021f. 387
388 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE FIGURE 6-25â Type of studies identified within autoimmune disease grant ab- stracts (N=1,127). NOTE: Percentages in the figure add up to be more than 100 percent because grants could be tagged with more than one research characteristic. SOURCE: NIH, 2021f. Study Section Analysis Investigator-initiated research (R01) grants are the most common research grants funded (Figure 6-9). As noted in Chapter 5, study sections review applications for these grants, with study section peer reviewers responsible for assigning priority scores based on scientific merit. Peer reviewers draw upon their expertise in investigating line(s) of research comparable to those under review to assign scores that distinguish the very best applications from the weaker ones. The committee used the NIH Center for Scientific Review (CSR) study section search tool to analyze study sections that review R01 grant appli- cations.14 As many as 100 different study sections may be involved in 14 The committee used the online CSR study section tool available at https://public.csr. nih.gov/StudySections, accessed November 24, 2021. The committee entered the name of each of the select autoimmune diseases of committee interest into the study section search field to identify the names of its associated chartered study sections. Only chartered study sections were included because they review most investigator- initiated research grant applications. The total number of chartered study sections for all select diseases (de-duplicated) was then tallied. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 389 reviewing unsolicited investigator-initiated research grant applications focusing on the select autoimmune diseases the committee chose to exam- ine. Given that such a large number of diverse study sections can poten- tially review autoimmune disease grant applications, CSR should ensure that individual study section rosters include the appropriate expertise, including expertise for reviewing animal and human studies, to provide the proper review of these applications. Table 6-1015 provides a snapshot of data generated by the RePORTER Matchmaker tool. The table shows study sectionsâthe names of which appear in the far left columnâthat reviewed funded grants focusing on the autoimmune diseases of interest to the committee; the table reflects a two-year period.16,17 The table identifies those study sections that reviewed the most funded grants for each disease of focus according to a bar graph RePORTER automatically generates to provide this informa- tion; the number of grants are indicated in the corresponding cells. One to three study sections reviewed the majority of funded grants for the two years, suggesting that this more limited number of study sections has the correct expertise for review of autoimmune disease grant applications. The committee notes that a more valuable analysis would have been to identify, for a given period, the grant applications that were reviewed for the select diseases regardless of whether they were approved. This would have provided a better baseline for analyzing patterns of review by the study sections. However this information was not available. The most common study sections responsible for the grant applications in this analysis were: Gastrointestinal Mucosal Pathobiology; Hypersensi- tivity, Autoimmune and Immune-Mediated Diseases; Arthritis, Connec- tive Tissue and Skin; Oral, Dental and Craniofacial Science; Cellular and Molecular Immunology B; Clinical Neuroimmunology and Brain Tumor; Innate Immunity and Inflammation; Cellular and Molecular Biology of Glia; Clinical and Integrative Diabetes and Obesity; Cellular Aspects of Obesity and Diabetes; and Hepatobiliary Pathophysiology. 15 SeeAppendix G for methodology. 16 The committee used the RePORTER Matchmaker search tool available at https://re- porter.nih.gov/matchmaker, accessed December 3, 2021. The committee entered the name of each of the select autoimmune diseases of committee interest into the field to yield the number of projects associated with that disease. The user then activated the Active Projects feature and selected 2019 and 2020 in the Fiscal Year dropdown. RePORTER then generated a graph of the study sections that had reviewed the most grants for that autoimmune disease. The study sections appearing in the graph, and the number of grants each study section reviewed, constitute the data included in Table 6-8. 17 Data of this nature change in the RePORTER system over time. For its analysis, the committee selected active projects; as projects conclude, they are no longer generated when the âactiveâ option is chosen. PREPUBLICATION COPYâUncorrected Proofs
TABLE 6-10â Chartered Study Sections that Reviewed Funded Grants (FY 2019â2020) According to Select 390 Autoimmune Diseases* Â Celiac SjÃ¶grenâs Psoria- Crohnâs Hashimotoâs SLE APS RA IBD Dis- PBC MS T1D Disease sis Disease Thyroiditis ease Gastrointestinal Muco- 25 1 13 sal Pathobiology Hypersensitivity, Auto- immune and Immune- 11 6 6 9 Mediated Diseases Arthritis, Connective 8 6 3 Tissue and Skin Oral, Dental and Cra- 2 7 4 niofacial Science Cellular and Molecular 3 1 4 3 Immunology B Clinical Neuroimmu- nology 11 and Brain Tumor Innate Immunity 4 3 3 and Inflammation PREPUBLICATION COPYâUncorrected Proofs Cellular and Molecular 8 Biology of Glia
Â Celiac SjÃ¶grenâs Psoria- Crohnâs Hashimotoâs SLE APS RA IBD Dis- PBC MS T1D Disease sis Disease Thyroiditis ease Clinical and Integrative 8 Diabetes and Obesity Cellular Aspects of 6 Diabetes and Obesity Hepatobiliary Patho- 6 physiology Skeletal Biology and 3 Developmental Disease Diseases and Pathol- ogy 2 of the Visual System Molecular and Cellular 2 Endocrinology Atherosclerosis and Inflammation of the 1 Cardiovascular System Cellular Signaling and Regulatory Sys- 1 PREPUBLICATION COPYâUncorrected Proofs tems continued 391
TABLE 6-10âContinued 392 Â Celiac SjÃ¶grenâs Psoria- Crohnâs Hashimotoâs SLE APS RA IBD Dis- PBC MS T1D Disease sis Disease Thyroiditis ease Genetics of 1 Health and Disease Hemostasis, Thrombo- sis and Blood Transfu- 1 sion Immunology and 1 Host Defense Macromolecular Struc- Â Â Â Â Â Â Â Â Â Â 1 ture and Function B *Table does not reflect all funded grants; it reflects funded grants portrayed in RePORTER-generated graphs that depicted the study sections that reviewed the most grants for the disease-specific searches. Table reflects data available as of October 5, 2021. NOTE: APS, antiphospholipid syndrome; IBD, inflammatory bowel disease; MS, multiple sclerosis; PBC, primary biliary cholangitis; RA, rheuma- toid arthritis; SLE, systemic lupus erythematosus; T1D, type 1 diabetes SOURCE: NIH, 2021f. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 393 INDICATORS OF NIH AUTOIMMUNE RESEARCH PORTFOLIO ACCOMPLISHMENT The statement of task directed the committee to include NIH accom- plishments in its report. The committee addressed this task by conducting a high-level review of a number of activities and measures that reflect progress in research (clinical trials and patents), and indicators of scien- tific performance, quality, and influence on the research field (bibliometric indicators). The committee describes the results of its examination below. Clinical Trials Results of biomedical research on autoimmune disease can yield opportunities to improve the prevention, detection, and treatment of these diseases. Clinical trials, also known as interventional studies, translate basic science knowledge for use in clinical care (NLM, 2021a). Clinical trials focus on developing, testing, and implementing diagnostics and therapeutics across a wide range of diseases and conditions to evaluate the effects of the interventions on safety and health-related outcomes (NLM, 2021a). The committee examined clinical trial activity by autoim- mune disease as one measure of research portfolio advancement. The committee obtained clinical trial data from clinicaltrials.gov18 and linked clinical trials to the grants associated with the committeeâs autoim- mune diseases of interest. Clinical trials were de-duplicated using their Clinical Trial ID and included based on their relevance to the committeeâs specific diseases of interest and autoimmune disease as a broader category (âother autoimmune diseaseâ). Ultimately, the committee identified 353 autoimmune disease clinical trials between filing year 2008 and 2020. The âother autoimmune diseaseâ category represents approximately 27 per- cent of the clinical trials. The remaining 73 percent were associated with one or more autoimmune disease. Figure 6-2619 shows the number of clinical trials by disease from fil- ing years 2008â2020. The top five autoimmune disease categories with the most clinical trials over the study period were type 1 diabetes (38.7 percent), other autoimmune disease (26.6 percent), rheumatoid arthritis (10.3 percent), multiple sclerosis (5.8 percent), and IBD (5.5 percent). Each of the remaining autoimmune diseases accounted for less than 5 percent of clinical trials over this period. Clinical trials were fewer for the remain- ing autoimmune diseases. 18Grants with an RCDC code for âAutoimmune Diseaseâ obtained from NIH RePORTER for Fiscal Year 2008 (October 1, 2008âSeptember 30, 2008) through Fiscal Year 2020 (October 1, 2019âSeptember 30, 2020). 19 See Appendix G for methodology. PREPUBLICATION COPYâUncorrected Proofs
394 FIGURE 6-26â Clinical trials by autoimmune disease, 2008â2020 (N=353). PREPUBLICATION COPYâUncorrected Proofs NOTE: Percentages in the figure add up to be more than 100 percent because clinical trials can be associated with more than one autoimmune disease. SOURCES: NIH, 2021c, 2021f.
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 395 Out of the 353 clinical trials pertaining to autoimmune disease, 20 are phase 4 clinical trials. A phase 4 clinical trial is a âphase of research to describe clinical trials occurring after the Food and Drug Administra- tion (FDA) has approved a drug for marketing. They include postmarket requirement and commitment studies that are required of or agreed to by the study sponsor, and gather additional information about a drugâs safety, efficacy, or optimal useâ(NLM, 2021a). Table 6-11 lists select phase 4 clinical trials. Publications The research community often looks to publication citations and other bibliometric measures as indicators of scientific performance, quality, and influence on a research field. The committee selected a number of these measures to examine the performance of the autoimmune disease research portfolio from 2008â2020. These indicators include the number of publications associated with funded grants, relative citation ratio, and journal impact factor. The committee conducted a bibliometric analysis of publications in PubMed associated with autoimmune disease-associated grant numbers in an effort to characterize scientific productivity and impact. Figure 6-2720 shows publications by disease category per year. Of the autoimmune dis- eases examined, the four diseases associated with the greatest number of publications over the 2008â2020 period were other autoimmune disease TABLE 6-11â Phase 4 Clinical Trials, Autoimmune Disease Prevention or Treatment Condition or Primary Official Title Disease Purpose RHYTHM (RHeumatoid Arthritis studY of THe Myocardium): How Rheumatoid Arthritis (RA) Rheumatoid Prevention and Tumor Necrosis Factor (TNF) Inhibitors Affect Arthritis the Myocardial Structure and Function. New Onset Type 1 Diabetes: Role of Exenatide Type 1 Diabetes Treatment Multicenter Open-label Study Evaluating the Inflammatory Bowel Safety and Efficacy of Standardized Initial Therapy Disease Using Either Mesalamine or Corticosteroids Then Treatment (Ulcerative Colitis) Mesalamine to Treat Children and Adolescents With Newly Diagnosed Ulcerative Colitis. SOURCES: NIH, 2018, 2020b, 2021c, 2021e. 20 See Appendix G for methodology. PREPUBLICATION COPYâUncorrected Proofs
396 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE (27.7 percent), IBD (22.5 percent), type 1 diabetes (18.2 percent), and mul- tiple sclerosis (16.1 percent). Figure 6-2821 shows the trends in autoimmune disease publications. Between publication year 2008 and 2020, other autoimmune disease publi- cations (light purple) generally trended upward and had the most publica- tions overall with an average of 3,398 per year. Publications associated with IBD (yellow) had the greatest number of publications among the commit- teeâs diseases of interest but appear to have peaked in 2014. Publications associated with type 1 diabetes (black), multiple sclerosis (dark purple), and systemic lupus erythematosus (light blue) have also trended downward. The Relative Citation Ratio (RCR) is a metric developed within the NIH Office of Portfolio Analysis (OPA). RCR ârepresents the field- and time-normalized citation rateâ to the expected citation rate based upon the articleâs co-citation network of NIH-funded publications (Hutchins et al., 2016; NIH, 2021d). A publication with an RCR of 1 means that it has the same influence as the average article. The RCR metric can be used to determine the allocation of research funding and the extent to which NIH awardees âmaintain high or low levels of influence on their respec- tive fields of researchâ (Aksnes et al., 2019; Hutchins et al., 2016). RCR is often used under the assumption that citations are a proxy for quality; however, articles can be cited for a variety of reasons and RCR does not take the specific context of a citation into account (NIH Library, 2020). This counters the argument that RCR, alone, is a measure of quality. Table 6-1222 shows the publications with RCRs by disease. IBD publica- tions had the highest average RCR of 3.029 and are therefore three times as influential as the average article according to this metric. Although primary biliary cholangitis publications had the lowest average RCR of 1.894, they are still approximately twice as influential as the average article. Journal impact factor (JIF) is âa measure of the frequency with which the average article in a journal has been cited in a particular year and it is used to measure the importance or rank of a journal by calculating the times its articles are citedâ (University of Illinois Chicago Library, 2016). The scientific impact of an individual article is unrelated to the impact factor of a journal (The University of Texas MD Anderson Cancer Center, 2021), and JIF is a measure of journal quality exclusively. In the context of evaluating NIHâs autoimmune disease portfolio, the committee focused on publications resulting from NIH-funded autoimmune disease research and the quality of the journals in which they are published. Figure 6-2923 shows average JIF for the 10 journals with the highest JIF for all projects. Of the 159,416 autoimmune disease-related publications, 21 See Appendix G for methodology. 22 See Appendix G for methodology. 23 See Appendix G for methodology. PREPUBLICATION COPYâUncorrected Proofs
FIGURE 6-27â Publications by autoimmune disease, 2008â2020 (N=159,416). PREPUBLICATION COPYâUncorrected Proofs NOTE: Percentages in the figure add up to be more than 100 percent because publications can be associated with more than one autoimmune disease. SOURCES: Clarivate, 2021; NIH, 2015, 2021f; NLM, 2021b. 397
398 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-28â Number of autoimmune disease publications by disease and year, 2008â2020. SOURCES: Clarivate, 2021; NIH, 2015, 2021f; NLM, 2021b.
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 399 TABLE 6-12â Publications with RCRs by Autoimmune Disease, 2008â 2020 (N=152,286) Publication Count Autoimmune Disease with RCR Mean Median Range Inflammatory bowel disease 34,540 (22.7%) 3.029 1.366 0 to 634.738 Other autoimmune disease 41,996 (27.6%) 2.445 1.281 0 to 275.191 Celiac disease 4,493 (3%) 2.387 1.274 0 to 61.164 Rheumatoid arthritis 23,497 (15.5%) 2.379 1.281 0 to 211.184 Autoimmune thyroid disease 1,724 (1.2%) 2.365 1.200 0 to 91.059 Psoriasis 6,539 (4.3%) 2.360 1.278 0 to 213.283 Multiple sclerosis 24,841 (16.4%) 2.349 1.228 0 to 216.311 Type 1 diabetes 27,691 (18.2%) 2.207 1.186 0 to 621.789 Systemic lupus erythema- 24,671 (16.3%) 2.175 1.205 0 to 621.789 tosus Antiphospholipid syndrome 772 (0.6%) 2.164 1.269 0 to 38.859 SjÃ¶grenâs disease 3,523 (2.4%) 2.093 1.233 0 to 43.621 Primary biliary cholangitis 247 (0.2%) 1.894 1.183 0 to 31.923 NOTES: Publications must be 2-3 years old in order to have enough citations to calculate an RCR. RCR, Relative Citation Ratio. SOURCES: Clarivate, 2021; NIH, 2015, 2021f; NLM, 2021b. 63 percent (101,199 of 159,416) had JIF data. The size of the bubble repre- sents the number of publications in the journal, while the location of the bubble on the y-axis shows the JIF relative to each other. Although Nature (dark gray) published the most articles between 2008 and 2020, Chemical Reviews (brown) has the highest JIF (43.9). In most fields, the impact fac- tor of 10 or greater is considered an excellent score while 3 is flagged as good and the average score is less than 1 (SCI Journal, 2021). Patents A patent grants a property right to the inventor and prohibits others from offering, selling, or importing that invention (USPTO, 2018). Patents granted as a result of NIH-funded autoimmune disease research aim to encourage and protect biomedical innovation and may serve as a proxy for knowledge generation and translational value in the field (Kalutkie- wicz and Ehman, 2014). The committee examined patents and patent applications by autoimmune diseases. The committee obtained patent data linked to the grants associated with the committeeâs autoimmune disease of interest from the United PREPUBLICATION COPYâUncorrected Proofs
400 FIGURE 6-29â Average JIF for the 10 Journals with the Highest JIF for All Projects, 2008â2020. NOTES: Because of the vast differences in the size of citation pools for general journals (large citation pools) versus very special- PREPUBLICATION COPYâUncorrected Proofs ized journals (smaller citation pools), caution should be taken when comparing general and specialized journals without normal- ization. JIF, Journal Impact Factor. SOURCES: Clarivate, 2021; NIH, 2015, 2021f; NLM, 2021b.
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 401 States Patent and Trademark Office (USPTO) at uspto.gov. A total of 4,113 patent applications and patents were associated with NIH grants fund- ing research in autoimmune diseases, of which 60 percent (2,470 of 4,113) were patent applications and 40 percent (1,643 of 4,113) were granted applications (patents). All were included in the analysis. A total of 30 percent of the patents and patent applications were associated with only one disease category. The remaining 70 percent were associated with more than one disease category. Figure 6-3024 shows the number of patent applications by disease for filing years 2008â2020. The top three autoimmune disease categories with the most patent applications were other autoimmune disease (30.3 percent), multiple sclerosis (22.8 percent), and IBD (19.8 percent). Fewer patent applications were filed for the remaining autoimmune diseases. Figure 6-3125 shows the granted patents by disease for filing years 2008â2020. The top three disease categories with the most patents were other autoimmune disease (29.1 percent), multiple sclerosis (22.7 percent), and IBD (18.4 percent). The ultimate outcome of clinical and biomedical research is an observ- able impact on the health and wellbeing of individuals. This downstream effect is a result of fundamental scientific knowledge âapplied to develop actionable interventions that are implemented to enhance health, lengthen life, and reduce illness and disabilityâ (NIH, 2014). Publications dissemi- nated throughout the scientific community often report the outcomes of clinical and biomedical research, and the number of publications result- ing from autoimmune disease-related research is astounding, as seen by the thousands of relevant autoimmune-related publications produced between 2008 and 2020. The committee was unable to perform a comprehensive assessment of research accomplishments and successes and therefore was unable to assess clinical and biomedical achievements as a measure of knowledge in the field beyond quantifying publications, patents, and clinical tri- als. Another way to assess achievements is to determine how research translates into clinical care and treatment of individuals, but this too is an immense undertaking. Instead, theÂ committee provides a number of illustrative research findings associated with the research portfolio that have the potential to improve the health and healthcare of individuals living with autoimmune diseases in Table 6-13.26 24 See Appendix G for methodology. 25 See Appendix G for methodology. 26 Autoimmune Disease Research Highlights were collected from NIH biennial and trien- nial reports to congress, and NIH websites. PREPUBLICATION COPYâUncorrected Proofs
402 PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-30â Patent Applications by Disease, 2008â2020 (N=2,470). NOTE: Percentages in the figure add up to be more than 100 percent because patents can be associated with more than one auto- immune disease. SOURCES: NIH, 2021f; USPTO, 2018.
PREPUBLICATION COPYâUncorrected Proofs FIGURE 6-31â Patents by Disease, 2008â2020 (N=1,643). NOTE: Percentages in the figure add up to be more than 100 percent because patents can be associated with more than one auto- immune disease. SOURCES: NIH, 2021f; USPTO, 2018. 403
404 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-13â Autoimmune Disease Research Highlights Finding Description SjÃ¶grenâs disease Investigators have found that a high level of interferons (IFNs, that is, proteins produced in the inflammatory response to infections) to be associated with a more severe form of SjÃ¶grenâs disease for more than 50 per- cent of patients studied. This finding paves the way for Research on Interferons Could âprecision-based medicine,â a customized treatment Identify Individuals with approach which tailors health care based on a personâs SjÃ¶grenâs Disease Most Likely genes to those patients most likely to respond to certain to Respond to Treatment therapies, such as anti-IFN treatments. In addition, it could improve the selection of for clinical trials. âStrati- ficationâ of candidates is particularly important given differences among patients with SjÃ¶grenâs disease. Such heterogeneity complicates disease classification, assign- ment of disease mechanism and selection of therapy (Hall et al., 2015). Systemic lupus erythematosus Unique âimmune signaturesâ can identify pregnant patients with SLE who could suffer such complications as preeclampsia, high blood pressure and damage to organ systems such as the liver and kidneys, which endanger the mother, and death of a fetus as well as issues with fetal growth and preterm delivery. Such Immunomonitoring Can Pre- outcomes affect over one-fifth of SLE pregnancies. dict Complications of Lupus Researchers concluded that immune signatures, more Pregnancies accurate than clinical assessments, can predict the development of preeclampsia and adverse outcomes for the fetus. Their findings provide a framework for developing treatments to reduce morbidity and mor- tality complications in pregnant patients with lupus (Hong et al., 2019). continued PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 405 TABLE 6-13â Continued Multiple sclerosis Research which transplanted stem cells for treatment of MS led to positive outcomes for patients with the relapsing form of MS. Almost half of those in the study remained free from neurological progression of the disease five years after the transplant. Better outcomes such as improvement in bone marrow and âresettingâ of the immune system are associated with such factors for patients as younger age, fewer prior immunothera- Stem Cell Transplants Leads pies and not having reached high disability levels. For to Positive Outcomes for Mul- researchers, such results justify a future clinical trial tiple Sclerosis Patients on stem cell transplants for treating MS including an evaluation of safety and efficacy against approved therapies of high efficacy. Another trial could address whether this therapy can reduce the progression of disability in patients with a progressive form of MS that is worsening neurological function from the onset of symptoms without relapses or remissions (Muraro et al., 2017). Type 1 diabetes Study of treatment with teplizumab found that this immune system-modulating drug delayed the onset of type 1 diabetes in high-risk but nondiabetic relatives of patients with diabetes. The delay of progression to type 1 diabetes is particularly important given that it Early Preventive Treatment is the second most common disease of childhood after Delays Onset of Type 1 Dia- asthma. At-risk children progress to type 1 diabetes betes more rapidly than adults. Once this condition develops, children can face such challenges as managing it on a daily basis and those who are not treated face life- threatening complications. Building on this study, next steps include testing the long-term efficacy and safety of teplizumab (Herold et al., 2019). PREPUBLICATION COPYâUncorrected Proofs
406 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE TABLE 6-13â Continued A clinical trial at four U.S. pediatric centers found that a new artificial pancreas system effectively manages blood glucose in children as young as age six. The artificial pancreas, also known as a âclosed-loop con- trol,â is an âall-in-oneâ diabetes management system Artificial Pancreas System which tracks blood glucose levels and automatically Controls Diabetes in Children delivers insulin when needed. By replacing reliance on fingerstick testing with delivery of insulin by multiple daily injections (or pump controlled by the patient or caregiver), this system can improve the quality of life and disease management for youth (Breton et al., 2020). Rheumatoid arthritis Research has found that women with lung diseases such as asthma or chronic obstructive pulmonary disease (COPD) have an increased risk of develop- Lung Diseases Such as Asthma ing rheumatoid arthritis (RA). This is independent of Increase the Risk of Rheuma- smoking which is a strong environmental risk factor for toid Arthritis the development of RA. Early detection of RA through monitoring of such patients could mean lowering the risk of long-term adverse consequences in the future (Ford et al., 2020). Inflammatory bowel disease Because irritable bowel disease makes it difficult for food nutrients to be absorbed, growth in children who have ulcerative colitis (a type of IBD limited to the co- lon) can be stunted due to malnutrition. The PROTECT Study (Predicting Response to Standardized Pediatric Colitis Therapy) has examined responses to treatment Discovery of Biomarker Holds by children newly diagnosed with ulcerative colitis. Potential for Improved Treat- This study determined that the presence in the blood ment of Ulcerative Colitis in of a biomarker called pANCA (Perinuclear anti-neu- Children trophil cytoplasmic antibody) is associated with more extensive resistance to therapy for this disease. These are antibodies to a type of white blood cell called neu- trophil. The identification of this biomarker indicates its potential as a diagnostic tool for planning individual treatments for children with this disease (Spencer et al., 2018). continued PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 407 TABLE 6-13â Continued Clinical benefits of certain treatments which can block the inflammatory response in Crohnâs disease have not worked for all patients and drug trials for patients with IBD have had limited success in recent decades. As a result, radical measures such as surgical removal of af- fected areas in the small intestine may be necessary. Recent research identifies a distinctive combination of cells in those people with Crohnâs disease who do not respond to âanti-TNFâ drugs. (TNF or tumor necrosis Identification of Unique Cel- factor refers to an inflammation causing protein in the lular Signatures for Crohnâs body.) Analysis of how the cells communicate with Disease Patients May Improve each other showed that this particular cellular com- Treatment in the Future bination does not rely solely upon the tumor necrosis factor to maintain gut inflammation. This may explain why TNF-blocking drugs are ineffective. This analysis also identifies several other molecular targets for other potential therapies that, if used in combination with TNF-blocking drugs might be able to prevent inflam- mation in people with Crohnâs disease who do not respond to anti-TNF medications alone. Such enhanced understanding of differences in cellular makeup can shed light on the nature of Crohnâs disease and help predict which treatments might be effective (Martin et al., 2019). SUMMARY In reviewing NIHâs research portfolio on autoimmune diseases, the committee employed a general framework that considered the inputs (spending), activities (research conducted), and outputs (clinical trials, patents and other indicators) of NIHâs investment in autoimmune disease research. Spending on autoimmune diseases as a percent of overall NIH obligations has remained at only 2.6 percent between 2013 and 2020. This is in marked contrast to increases seen in overall NIH obligations during the same time period. In addition, the distribution of this funding for autoimmune diseases indicates that certain ICs dominate overall spend- ing on research and training and the types of research activities funded. NIH may need to reconsider the current strong focus on investigator- initiated research in order to target areas of high priority and effectively address the long-term, complex, and heterogeneous nature of autoim- mune diseases. Regarding the activities conducted under funded autoimmune dis- ease research grants, the multiple methods the committee used yielded PREPUBLICATION COPYâUncorrected Proofs
408 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE useful information at different levels of specificity. However, metrics are not available for evaluating the overall research portfolio for autoimmune diseases. The outputs of NIHâs investment in autoimmune disease research can be measured in a variety of ways, including clinical trials (the translation of research knowledge into interventions), publications, and the number of patents associated with autoimmune research grants (an important indicator of innovation). There is a greater percentage of clinical trials from filing years 2008â2020 for such autoimmune diseases as type 1 dia- betes, SLE, IBD, and rheumatoid arthritis, with a much smaller percentage seen for other autoimmune diseases. In general, the knowledge associ- ated with existing research grants has been successfully disseminated to the research community through publications in well-regarded scientific journals. In terms of patent applications, filings occur primarily for some autoimmune diseases with far fewer filings for others. In general, findings related to research outputs suggest the need for a nuanced and in-depth examination of why progress via clinical trials and patent filings does not seem to have been made for certain autoimmune diseases. Given the findings of Chapter 6, the committee concludes that the absence of an overarching strategic plan with concrete metrics makes it difficult to assess the distribution of funding by IC or disease. The com- mittee also concludes that the relatively small percentage of NIH funding devoted to autoimmune disease research and how it distributed could be a significant factor in hampering scientific progress on diseases that affect 23 million people. REFERENCES Aksnes, D. W., L. Langfeldt, and P. Wouters. 2019. Citations, citation indicators, and research quality: An overview of basic concepts and theories. SAGE Open 9(1):2158244019829575. Bittermann, A., and A. Fischer. 2018. How to identify hot topics in psychology using topic modeling. Zeitschrift fÃ¼r Psychologie 226(1):3â13. Blei, D. M., A. Y. Ng, and M. I. Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research 3:993â1022. Breton, M. D., L. G. Kanapka, R. W. Beck, L. Ekhlaspour, G. P. Forlenza, E. Cengiz, M. Schoel- wer, K. J. Ruedy, E. Jost, L. Carria, E. Emory, L. J. Hsu, M. Oliveri, C. C. Kollman, B. B. Dokken, S. A. Weinzimer, M. D. DeBoer, B. A. Buckingham, D. Chernavvsky, R. P. Wad- wa, for the iDCL Trial Research Group. 2020. A randomized trial of closed-loop control in children with type 1 diabetes. The New England Journal of Medicine 383(9):836â845. https://doi.org/10.1056/nejmoa2004736. Clarivate. 2021. Web of science. https://clarivate.com/webofsciencegroup/solutions/web- of-science/ (accessed December 14, 2021). Cristian, J. 2020. Topic modeling LDA using textminer and tidytext. https://rpubs.com/jojo- ecp/643113 (accessed December 14, 2021). Ford, J. A., X. Liu, S. H. Chu, B. Lu, M. H. Cho, E. K. Silverman, K. H. Costenbader, C. A. Camargo, Jr., and J. A. Sparks. 2020. Asthma, chronic obstructive pulmonary disease, and subsequent risk for incident rheumatoid arthritis among women: A prospective cohort study. Arthritis & Rheumatology 72(5):704â713. PREPUBLICATION COPYâUncorrected Proofs
INSTITUTE AND CENTER AUTOIMMUNE DISEASE RESEARCH 409 Goldmuntz, E. 2020. Charge to the comittee. Paper read at NASEM Committee for the As- sessment of NIH Research on Autoimmune Diseases: Meeting 1, November 18, 2020, Webinar. Hall, J. C., A. N. Baer, A. A. Shah, L. A. Criswell, C. H. Shiboski, A. Rosen, and L. Casciola- Rosen. 2015. Molecular subsetting of interferon pathways in SjÃ¶grenâs syndrome. Ar- thritis & Rheumatology 67(9):2437â2446. Herold, K. C., B. N. Bundy, S. A. Long, J. A. Bluestone, L. A. DiMeglio, M. J. Dufort, S. E. Gitelman, P. A. Gottlieb, J. P. Krischer, P. S. Linsley, J. B. Marks, W. Moore, A. Moran, H. Rodriguez, W. E. Russell, D. Schatz, J. S. Skyler, E. Tsalikian, D. K. Wherrett, A. G. Ziegler, C. J. Greenbaum, and G. Type 1 Diabetes TrialNet Study. 2019. An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes. The New England Journal of Medicine 381(7):603â613. Hodge, D. 2021. NIH peer review, a CSR perspective. Paper read at NASEM Committee for the Assessment of NIH Research on Autoimmune Diseases: Meeting 2 (Continuation), February 1, 2021, Webinar. Hong, S., R. Banchereau, B. L. Maslow, M. M. Guerra, J. Cardenas, J. Baisch, D. W. Branch, T. F. Porter, A. Sawitzke, C. A. Laskin, J. P. Buyon, J. Merrill, L. R. Sammaritano, M. Petri, E. Gatewood, A. M. Cepika, M. Ohouo, G. Obermoser, E. Anguiano, T. W. Kim, J. Nulsen, D. Nehar-Belaid, D. Blankenship, J. Turner, J. Banchereau, J. E. Salmon, and V. Pascual. 2019. Longitudinal profiling of human blood transcriptome in healthy and lupus pregnancy. Journal of Experimental Medicine 216(5):1154â1169. Hutchins, B. I., X. Yuan, J. M. Anderson, and G. M. Santangelo. 2016. Relative citation ratio (RCR): A new metric that uses citation rates to measure influence at the article level. PLOS Biology 14(9):e1002541. Kalutkiewicz, M. J., and R. L. Ehman. 2014. Patents as proxies: NIH hubs of innovation. Nature Biotechnology 32(6):536â537. https://www.acadrad.org/wp-content/uploads/ 2016/06/Patents-as-Proxies-article.pdf (accessed March 3, 2022). Martin, J. C., C. Chang, G. Boschetti, R. Ungaro, M. Giri, J. A. Grout, K. Gettler, L. S. Chuang, S. Nayar, A. J. Greenstein, M. Dubinsky, L. Walker, A. Leader, J. S. Fine, C. E. Whitehurst, M. L. Mbow, S. Kugathasan, L. A. Denson, J. S. Hyams, J. R. Friedman, P. T. Desai, H. M. Ko, I. Laface, G. Akturk, E. E. Schadt, H. Salmon, S. Gnjatic, A. H. Rahman, M. Merad, J. H. Cho, and E. Kenigsberg. 2019. Single-cell analysis of Crohnâs disease lesions identifies a pathogenic cellular module associated with resistance to anti-tnf therapy. Cell 178(6):1493â1508 e1420. McNamara, J. 2021. Autoimmune disease research supported by extramural NIAID. Paper read at NASEM Committee for the Assessment of NIH Research on Autoimmune Diseases: Meeting 2 (Continuation), February 1, 2021, Webinar. Muraro, P. A., M. Pasquini, H. L. Atkins, J. D. Bowen, D. Farge, A. Fassas, M. S. Freedman, G. E. Georges, F. Gualandi, N. Hamerschlak, E. Havrdova, V. K. Kimiskidis, T. Kozak, G. L. Mancardi, L. Massacesi, D. A. Moraes, R. A. Nash, S. Pavletic, J. Ouyang, M. Rovira, A. Saiz, B. Simoes, M. Trneny, L. Zhu, M. Badoglio, X. Zhong, M. P. Sormani, and R. Saccardi, for the Multiple SclerosisâAutologous Hematopoietic Stem Cell Transplanta- tion (MS-AHSCT) Long-term Outcomes Study Group. 2017. Long-term outcomes after autologous hematopoietic stem cell transplantation for multiple sclerosis. JAMA Neurol- ogy 74(4):459â469. https://doi.org/10.1001/jamaneurol.2016.5867. NIH (National Institutes of Health). 2015. SPIRES. https://dpcpsi.nih.gov/sites/default/ files/opa/document/Posters/Tools/15%20Jordan%20SPIRES-OPA-Symposium-Post- er-Final-07212015.pdf (accessed December 14, 2021). NIH. 2018. Predicting response to standardized pediatric colitis therapy (PROTECT). https:// clinicaltrials.gov/ct2/show/NCT01536535?id=NCT01536535&draw=2&rank=1 (ac- cessed December 16, 2021). PREPUBLICATION COPYâUncorrected Proofs
410 ENHANCING NIH RESEARCH ON AUTOIMMUNE DISEASE NIH. 2019. Types of grant programs. https://grants.nih.gov/grants/funding/funding_pro- gram.htm (accessed September 3, 2021). NIH. 2020a. Estimates of funding for various research, condition, and disease categories (RCDC). https://report.nih.gov/funding/categorical-spending#/ (accessed April 12, 2021). NIH. 2020b. RHYTHM (formerly Escape II Myocardium) (RHYTHM). https://clinicaltrials. gov/ct2/show/NCT01548768 (accessed December 16). NIH. 2021a. About RCDC. https://report.nih.gov/funding/categorical-spending/rcdc (ac- cessed July 03, 2021). NIH. 2021b. Actual total obligations by institute and center: FY 2000âFY 2020. https://officeof- budget.od.nih.gov/pdfs/FY21/spending-hist/Actual%20Obligations%20By%20IC%20 FY%202000%20-%20FY%202020%20(V).pdf (accessed September 2, 2021). NIH. 2021c. Clinicaltrials.Gov is a database of privately and publicly funded clinical studies con- ducted around the world. https://clinicaltrials.gov/ (accessed May 8, 2021). NIH. 2021d. iCite: Influence module. https://icite.od.nih.gov/user_guide?page_id=ug_infl (accessed December 7, 2021). NIH. 2021e. New onset type 1 diabetes: Role of exenatide. https://clinicaltrials.gov/ct2/show/ study/NCT01269034?id=NCT01269034&draw=2&rank=1 (accessed December 16, 2021). NIH. 2021f. NIH reporter database. NIH Grants & Funding. 2021. Activity codes search results. https://grants.nih.gov/grants/ funding/ac_search_results.htm (accessed December 7, 2021). NIH Library. 2020. Week 11: Citation impact. https://www.youtube.com/watch?v= bxv0tzmbwxg (accessed December 7, 2021). NLM (National Library of Medicine). 2021a. Glossary of common site terms. https://clinical trials.gov/ct2/about-studies/glossary (accessed December 14, 2021). NLM. 2021b. Pubmed.Gov. https://pubmed.ncbi.nlm.nih.gov/ (accessed December 14, 2021). Park, J., M. Blume-Kohout, R. Krestel, E. Nalisnick, and P. Smyth. 2016. Analyzing NIH funding patterns over time with statistical text analysis. Palo Alto, CA: Association for the Advancement of Artificial Intelligence. Porturas, T., and R. A. Taylor. 2021. Forty years of emergency medicine research: Uncover- ing research themes and trends through topic modeling. American Journal of Emergency Medicine 45:213â220. SCI Journal. 2021. Whatâs a good impact factor & why it matters (with 2018/2019 impact factor ranking in 27 categories). https://www.scijournal.org/articles/good-impact-factor (ac- cessed December 7, 2021). Spencer, E. A., S. M. Davis, D. R. Mack, B. M. Boyle, A. M. Griffiths, N. S. LeLeiko, C. G. Sauer, D. J. Keljo, J. F. Markowitz, S. S. Baker, J. R. Rosh, R. N. Baldassano, M. Oliva- Hemker, M. D. Pfefferkorn, A. R. Otley, M. B. Heyman, J. D. Noe, A. S. Patel, P. A. Rufo, P. S. Group, M. Alison Marquis, T. D. Walters, M. H. Collins, S. Kugathasan, L. A. Denson, J. S. Hyams, and M. C. Dubinsky. 2018. Serologic reactivity reflects clinical expression of ulcerative colitis in children. Inflammatory Bowel Diseases 24(6):1335â1343. The University of Texas MD Anderson Cancer Center. 2021. Q. What is considered a good impact factor? https://mdanderson.libanswers.com/faq/26159 (accessed December 7, 2021). University of Illinois Chicago Library. 2016. Measuring your impact: Impact factor, citation analysis, and other metrics: Journal impact factor (if). https://researchguides.uic.edu/if/ impact (accessed December 7, 2021). USPTO (United States Patent and Trademark Office). 2018. General information concerning pat- ents. https://www.uspto.gov/patents/basics/general-information-patents (accessed December 7, 2021). PREPUBLICATION COPYâUncorrected Proofs