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Berger S, Moseholm KF, Hegelund ER, Tesch F, Nguyen MCS, Mortensen LH, Jensen MK, Schmitt J, Mukamal KJ. Association of Tumor Necrosis Factor-α Inhibitors with Incident Dementia: Analysis Based on Population-Based Cohort Studies. Drugs Aging 2024; 41:423-430. [PMID: 38609734 PMCID: PMC11093812 DOI: 10.1007/s40266-024-01112-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/17/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND AND OBJECTIVE Preliminary evidence suggests a possible preventive effect of tumor necrosis factor-α inhibitors (TNFi) on incident dementia. The objective of the analysis was to investigate the association between TNFi and the risk of incident dementia in a population undergoing treatment for rheumatological disorders. METHODS We followed patients aged ≥ 65 years with dementia and rheumatological conditions in two cohort studies, DANBIO (N = 21,538), a Danish clinical database, and AOK PLUS (N = 7112), a German health insurance database. We defined incident dementia using diagnostic codes and/or medication use and used Cox regression to compare the associations of TNFi with other rheumatological therapies on the risk of dementia. To ensure that the patients were receiving long-term medication, we included patients with rheumatic diseases and systemic therapies. RESULTS We observed similar trends towards a lower risk of dementia associated with TNFi versus other anti-inflammatory agents in both cohorts (hazard ratios were 0.92 [95% confidence interval 0.76, 1.10] in DANBIO and 0.89 [95% confidence interval 0.63, 1.24] in AOK PLUS, respectively). CONCLUSIONS Tumor necrosis factor-α inhibitors may decrease the risk of incident dementia although the association did not reach statistical significance in this analysis. Further research, ideally with randomization, is needed to gauge the potential of repurposing TNFi for dementia prevention and/or treatment.
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Affiliation(s)
- Saskia Berger
- Center for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
- Hospital Pharmacy, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstrasse 74, 01307, Dresden, Germany.
| | - Kristine F Moseholm
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Emilie R Hegelund
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Falko Tesch
- Center for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Minh Chau S Nguyen
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Laust H Mortensen
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Majken K Jensen
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jochen Schmitt
- Center for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Kenneth J Mukamal
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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2
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Xie W, Hou Y, Xiao S, Zhang X, Zhang Z. Association between disease-modifying antirheumatic drugs for rheumatoid arthritis and risk of incident dementia: a systematic review with meta-analysis. RMD Open 2024; 10:e004016. [PMID: 38413170 PMCID: PMC10900342 DOI: 10.1136/rmdopen-2023-004016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 02/05/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Dysregulation of several inflammatory cytokines including tumour necrosis factor (TNF) in dementia patients has also been identified as a key factor in the pathogenesis of rheumatoid arthritis (RA). We aimed to investigate the association of disease-modifying antirheumatic drugs (DMARDs) therapy for RA with risk of incident dementia. METHODS Electronic database searches of PubMed, EMBASE and Cochrane Library were performed. Observational studies that assessed the association of dementia with DMARDs in RA were included. Pooled risk ratios (RRs) with 95% CIs were used as summary statistic. The certainty of evidence was judged by using the Grading of Recommendations Assessment, Development and Evaluation system. RESULTS Overall, 14 studies involving 940 442 patients with RA were included. Pooled RR for developing dementia was 0.76 (95% CI 0.72 to 0.80) in patients taking biological DMARDs overall versus those taking conventional synthetic DMARDs, with 24% for TNF inhibitors (RR 0.76, 95% CI 0.71 to 0.82), 24% for non-TNF biologics (RR 0.76, 95% CI 0.70 to 0.83), separately. There was a significant subgroup effect among different types of TNF inhibitors (RR 0.58 [95%CI 0.53 to 0.65], 0.65 [95% CI 0.59 to 0.72], 0.80 [95% CI 0.72 to 0.88] for etanercept, adalimumab, infliximab, respectively; p value between groups=0.002). However, compared with non-users of DMARDs or investigative treatment, no significant effect on dementia incidence was observed in those receiving conventional synthetic DMARDs overall (RR 0.84, 95% CI 0.59 to 1.20), methotrexate (RR 0.78, 95% CI 0.54 to 1.12), hydroxychloroquine (RR 0.95, 95% CI 0.63 to 1.44), except for sulfasalazine (RR 1.27, 95% CI 1.06 to 1.50). CONCLUSIONS Biological DMARDs for RA are associated with decreased dementia risk, while protective effect is not observed in conventional synthetic DMARDs. Controlled clinical trials on TNF inhibitors are necessary to test their neuroprotective potentials.
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Affiliation(s)
- Wenhui Xie
- Department of Rheumatology and Clinical Immunology, Peking University First Hospital, Beijing, China
| | - Yue Hou
- Department of Geriatrics, Peking University First Hospital, Beijing, China
| | - Shiyu Xiao
- Department of Gastroenterology, University of Electronic Science and Technology, Chengdu, China
| | - Xiaolin Zhang
- Department of Geriatrics, Peking University First Hospital, Beijing, China
| | - Zhuoli Zhang
- Department of Rheumatology and Clinical Immunology, Peking University First Hospital, Beijing, China
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3
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Serafini S, Ferretti G, Monterosso P, Angiolillo A, Di Costanzo A, Matrone C. TNF-α Levels Are Increased in Patients with Subjective Cognitive Impairment and Are Negatively Correlated with β Amyloid-42. Antioxidants (Basel) 2024; 13:216. [PMID: 38397814 PMCID: PMC10886257 DOI: 10.3390/antiox13020216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/01/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
The role of tumor necrosis factor-α (TNF-α) in Alzheimer's disease (AD) has recently become a topic of debate. TNF-α levels increase in the blood of patients with AD, and amyloid beta (Aβ) plaques contain TNF-α deposits. The therapeutic efficacy of blocking TNF-α in patients with AD remains controversial as it is mostly based on preclinical studies. Thus, whether and how TNF-α contributes to amyloidogenic processes in AD is still an open question to be addressed. We analyzed plasma TNF-α and Aβ42 levels in patients with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD, and in healthy volunteers (HLT). In addition, we performed correlation analysis to evaluate whether changes in plasma TNF-α levels correlate with cognitive decline, Aβ42 levels, age, and BMI, which are all factors considered to contribute to or predispose individuals to AD. We found that TNF-α and Aβ42 plasma levels were higher in patients with AD than in HLT individuals. High TNF-α levels were also observed in patients with SCI, in whom TNF-α and Aβ42 levels were negatively correlated. Notably, TNF-α did not affect the amyloidogenic pathway in human microglial cultures exposed to 48 h of incubation, although it did trigger neuroinflammatory processes. These results imply that high TNF-α levels are more likely to be a clinical condition linked to AD than are direct contributors. Nonetheless, elevated levels of TNF-α in early-stage patients, like those with SCI and MCI, may provide a distinguishing feature for identifying clinical profiles that are at risk of having a poorer outcome in AD and could benefit from tailored therapies.
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Affiliation(s)
- Sara Serafini
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
| | - Gabriella Ferretti
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
| | - Paola Monterosso
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
| | - Antonella Angiolillo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100 Campobasso, Italy
| | - Alfonso Di Costanzo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100 Campobasso, Italy
| | - Carmela Matrone
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
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4
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Marr C, McDowell B, Holmes C, Edwards CJ, Cardwell C, McHenry M, Meenagh G, Teeling JL, McGuinness B. The RESIST Study: Examining Cognitive Change in Rheumatoid Arthritis Patients with Mild Cognitive Impairment Being Treated with a TNF-Inhibitor Compared to a Conventional Synthetic Disease-Modifying Anti-Rheumatic Drug. J Alzheimers Dis 2024; 99:161-175. [PMID: 38669538 DOI: 10.3233/jad-231329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Background Evidence suggests that TNF inhibitors (TNFi) used to treat rheumatoid arthritis (RA) may protect against Alzheimer's disease progression by reducing inflammation. Objective To investigate whether RA patients with mild cognitive impairment (MCI) being treated with a TNFi show slower cognitive decline than those being treated with a conventional synthetic disease-modifying anti-rheumatic drug (csDMARD). Methods 251 participants with RA and MCI taking either a csDMARD (N = 157) or a TNFi (N = 94) completed cognitive assessments at baseline and 6-month intervals for 18 months. It was hypothesized that those taking TNFis would show less decline on the primary outcome of Free and Cued Selective Reminding Test with Immediate Recall (FCSRT-IR) and the secondary outcome of Montreal Cognitive Assessment (MoCA). Results No significant changes in FCSRT-IR scores were observed in either treatment group. There was no significant difference in FCSRT-IR between treatment groups at 18 months after adjusting for baseline (mean difference = 0.5, 95% CI = -1.3, 2.3). There was also no difference in MoCA score (mean difference = 0.4, 95% CI = -0.4, 1.3). Conclusions There was no cognitive decline in participants with MCI being treated with TNFis and csDMARDs, raising the possibility both classes of drug may be protective. Future studies should consider whether controlling inflammatory diseases using any approach is more important than a specific therapeutic intervention.
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Affiliation(s)
- Calum Marr
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Bethany McDowell
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Clive Holmes
- Faculty of Medicine, University of Southampton, Southampton, UK
- Southern Health NHS Foundation Trust, Southampton, UK
| | - Christopher J Edwards
- Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Southampton Clinical Research Facility, Southampton, UK
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | | | | | - Gary Meenagh
- Northern Health and Social Care Trust, Antrim, UK
| | - Jessica L Teeling
- Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
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5
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Garmendia JV, De Sanctis CV, Das V, Annadurai N, Hajduch M, De Sanctis JB. Inflammation, Autoimmunity and Neurodegenerative Diseases, Therapeutics and Beyond. Curr Neuropharmacol 2024; 22:1080-1109. [PMID: 37898823 PMCID: PMC10964103 DOI: 10.2174/1570159x22666231017141636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/13/2023] [Accepted: 08/03/2023] [Indexed: 10/30/2023] Open
Abstract
Neurodegenerative disease (ND) incidence has recently increased due to improved life expectancy. Alzheimer's (AD) or Parkinson's disease (PD) are the most prevalent NDs. Both diseases are poly genetic, multifactorial and heterogenous. Preventive medicine, a healthy diet, exercise, and controlling comorbidities may delay the onset. After the diseases are diagnosed, therapy is needed to slow progression. Recent studies show that local, peripheral and age-related inflammation accelerates NDs' onset and progression. Patients with autoimmune disorders like inflammatory bowel disease (IBD) could be at higher risk of developing AD or PD. However, no increase in ND incidence has been reported if the patients are adequately diagnosed and treated. Autoantibodies against abnormal tau, β amyloid and α- synuclein have been encountered in AD and PD and may be protective. This discovery led to the proposal of immune-based therapies for AD and PD involving monoclonal antibodies, immunization/ vaccines, pro-inflammatory cytokine inhibition and anti-inflammatory cytokine addition. All the different approaches have been analysed here. Future perspectives on new therapeutic strategies for both disorders are concisely examined.
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Affiliation(s)
- Jenny Valentina Garmendia
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
| | - Claudia Valentina De Sanctis
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
| | - Viswanath Das
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
- The Czech Advanced Technology and Research Institute (Catrin), Palacky University, Olomouc, The Czech Republic
| | - Narendran Annadurai
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
| | - Marián Hajduch
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
- The Czech Advanced Technology and Research Institute (Catrin), Palacky University, Olomouc, The Czech Republic
| | - Juan Bautista De Sanctis
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, The Czech Republic
- The Czech Advanced Technology and Research Institute (Catrin), Palacky University, Olomouc, The Czech Republic
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6
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Tin A, Fohner AE, Yang Q, Brody JA, Davies G, Yao J, Liu D, Caro I, Lindbohm JV, Duggan MR, Meirelles O, Harris SE, Gudmundsdottir V, Taylor AM, Henry A, Beiser AS, Shojaie A, Coors A, Fitzpatrick AL, Langenberg C, Satizabal CL, Sitlani CM, Wheeler E, Tucker-Drob EM, Bressler J, Coresh J, Bis JC, Candia J, Jennings LL, Pietzner M, Lathrop M, Lopez OL, Redmond P, Gerszten RE, Rich SS, Heckbert SR, Austin TR, Hughes TM, Tanaka T, Emilsson V, Vasan RS, Guo X, Zhu Y, Tzourio C, Rotter JI, Walker KA, Ferrucci L, Kivimäki M, Breteler MMB, Cox SR, Debette S, Mosley TH, Gudnason VG, Launer LJ, Psaty BM, Seshadri S, Fornage M. Identification of circulating proteins associated with general cognitive function among middle-aged and older adults. Commun Biol 2023; 6:1117. [PMID: 37923804 PMCID: PMC10624811 DOI: 10.1038/s42003-023-05454-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 10/12/2023] [Indexed: 11/06/2023] Open
Abstract
Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets.
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Grants
- N01 HC095163 NHLBI NIH HHS
- RC2 HL102419 NHLBI NIH HHS
- HHSN268201500003C NHLBI NIH HHS
- UH3 NS100605 NINDS NIH HHS
- R01 HL103612 NHLBI NIH HHS
- 75N92020D00002 NHLBI NIH HHS
- U01 HL096812 NHLBI NIH HHS
- MC_UU_00006/1 Medical Research Council
- UF1 NS125513 NINDS NIH HHS
- 75N92020D00005 NHLBI NIH HHS
- N01AG12100 NIA NIH HHS
- N01HC95160 NHLBI NIH HHS
- R01 AG054076 NIA NIH HHS
- R01 HL120393 NHLBI NIH HHS
- BB/F019394/1 Biotechnology and Biological Sciences Research Council
- RF1 AG059421 NIA NIH HHS
- R01 HL131136 NHLBI NIH HHS
- N01 HC095168 NHLBI NIH HHS
- UL1 RR025005 NCRR NIH HHS
- R01 AG015928 NIA NIH HHS
- HHSN268201800004I NHLBI NIH HHS
- U01 HL080295 NHLBI NIH HHS
- N01HC95163 NHLBI NIH HHS
- N01 AG012100 NIA NIH HHS
- HHSN268201500001C NHLBI NIH HHS
- UL1 TR001079 NCATS NIH HHS
- N01 HC085082 NHLBI NIH HHS
- U01 HL096917 NHLBI NIH HHS
- R01 HL059367 NHLBI NIH HHS
- U01 HL130114 NHLBI NIH HHS
- HHSN268200800007C NHLBI NIH HHS
- R01 HL085251 NHLBI NIH HHS
- N01HC95169 NHLBI NIH HHS
- R01 NS087541 NINDS NIH HHS
- 75N92020D00001 NHLBI NIH HHS
- R01 HL086694 NHLBI NIH HHS
- R01 AG054628 NIA NIH HHS
- U01 HL096902 NHLBI NIH HHS
- R01 HL087652 NHLBI NIH HHS
- N01 HC095162 NHLBI NIH HHS
- U01 HG004402 NHGRI NIH HHS
- N01HC95164 NHLBI NIH HHS
- N01 HC085086 NHLBI NIH HHS
- N01HC55222 NHLBI NIH HHS
- R01 AG049607 NIA NIH HHS
- R01 AG065596 NIA NIH HHS
- N01 HC095165 NHLBI NIH HHS
- N01HC95162 NHLBI NIH HHS
- MR/R024227/1 Medical Research Council
- N01HC85086 NHLBI NIH HHS
- 75N92020D00003 NHLBI NIH HHS
- R01 HL105756 NHLBI NIH HHS
- N01HC95168 NHLBI NIH HHS
- N01 HC095169 NHLBI NIH HHS
- HHSN268201800003I NHLBI NIH HHS
- P30 DK063491 NIDDK NIH HHS
- HHSN268201800007I NHLBI NIH HHS
- HHSN268201700002C NHLBI NIH HHS
- R01 AG066524 NIA NIH HHS
- RF1 AG063507 NIA NIH HHS
- HHSN268201200036C NHLBI NIH HHS
- R01 HL144483 NHLBI NIH HHS
- HHSN268201800001C NHLBI NIH HHS
- HHSN268201700001I NHLBI NIH HHS
- R01 AG056477 NIA NIH HHS
- HHSN268201700004I NHLBI NIH HHS
- N01HC95165 NHLBI NIH HHS
- N01 HC095159 NHLBI NIH HHS
- U01 AG058589 NIA NIH HHS
- N01HC95159 NHLBI NIH HHS
- N01 HC095161 NHLBI NIH HHS
- HHSN268201500001I NHLBI NIH HHS
- HHSN271201200022C NIDA NIH HHS
- N01 HC025195 NHLBI NIH HHS
- N01HC95161 NHLBI NIH HHS
- UL1 TR001420 NCATS NIH HHS
- 75N92020D00004 NHLBI NIH HHS
- U01 HL096814 NHLBI NIH HHS
- P30 AG066509 NIA NIH HHS
- R01 HL132320 NHLBI NIH HHS
- 75N92020D00007 NHLBI NIH HHS
- P30 AG066546 NIA NIH HHS
- R01 AG033040 NIA NIH HHS
- MR/S011676/1 Medical Research Council
- U01 AG052409 NIA NIH HHS
- HHSN268201500003I NHLBI NIH HHS
- K01 AG071689 NIA NIH HHS
- 75N92021D00006 NHLBI NIH HHS
- R01 AG026307 NIA NIH HHS
- R01 AG020098 NIA NIH HHS
- HHSN268201700005C NHLBI NIH HHS
- HHSN268201700001C NHLBI NIH HHS
- N01HC85082 NHLBI NIH HHS
- HHSN268201700003C NHLBI NIH HHS
- N01 HC095166 NHLBI NIH HHS
- N01HC95167 NHLBI NIH HHS
- N01HC85083 NHLBI NIH HHS
- UH2 NS100605 NINDS NIH HHS
- N01HC25195 NHLBI NIH HHS
- 75N92019D00031 NHLBI NIH HHS
- U01 HL096899 NHLBI NIH HHS
- HHSN268201700004C NHLBI NIH HHS
- UL1 TR000040 NCATS NIH HHS
- HHSN268201700002I NHLBI NIH HHS
- HHSN268201700005I NHLBI NIH HHS
- P30 AG072947 NIA NIH HHS
- R01 AG025941 NIA NIH HHS
- Chief Scientist Office
- 75N92020D00006 NHLBI NIH HHS
- N01HC95166 NHLBI NIH HHS
- R01 AG023629 NIA NIH HHS
- R01 HL087641 NHLBI NIH HHS
- N01HC85079 NHLBI NIH HHS
- N01 HC085080 NHLBI NIH HHS
- UL1 TR001881 NCATS NIH HHS
- N01 HC095167 NHLBI NIH HHS
- HHSN268201800005I NHLBI NIH HHS
- N01HC85080 NHLBI NIH HHS
- HHSN268201700003I NHLBI NIH HHS
- HHSN268201800006I NHLBI NIH HHS
- N01 HC095164 NHLBI NIH HHS
- N01HC85081 NHLBI NIH HHS
- N01 HC095160 NHLBI NIH HHS
- The ARIC study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. Funding was also supported by 5RC2HL102419, R01NS087541 and R01HL131136. Neurocognitive data were collected by U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917 from the NIH (NHLBI, NINDS, NIA and NIDCD). Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This Cardiovascular Heath Study (CHS) research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, 75N92021D00006; and NHLBI grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, R01HL144483, and U01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629, R01AG15928, and R01AG20098 from the National Institute on Aging (NIA). AEF is supported by K01AG071689. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195, HHSN268201500001I and 75N92019D00031). This work was also supported by grant R01AG063507, R01AG054076, R01AG049607, R01AG059421, R01AG033040, R01AG066524, P30AG066546, U01 AG052409, U01 AG058589 from from the National Institute on Aging and R01 AG017950, UH2/3 NS100605, UF1 NS125513 from National Institute of Neurological Disorders and Stroke and R01HL132320. AGES has been funded by NIA contracts N01-AG012100 and HSSN271201200022C, NIH Grant No. 1R01AG065596-01A1, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). M. R. Duggan, T. Tanaka, J. Candia, K. A. Walker, L. Ferrucci, L.J. Launer, O. Meirelles are funded by the National Institute on Aging Intramural Research Program. This study was funded, in part, by the National Institute on Aging Intramural Research Program. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). The LBC1921 was supported by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society, and The Chief Scientist Office of the Scottish Government. Genotyping was funded by the BBSRC (BB/F019394/1). LBC1936 is supported by the Biotechnology and Biological Sciences Research Council, and the Economic and Social Research Council [BB/W008793/1], Age UK (Disconnected Mind project), and the University of Edinburgh. Genotyping was funded by the BBSRC (BB/F019394/1). The Olink® Neurology Proteomics assay was supported by a National Institutes of Health (NIH) research grant R01AG054628. Phenotype harmonization, data management, sample-identity QC, and general study coordination, were provided by the TOPMed Data Coordinating Center (3R01HL-120393-02S1), and TOPMed MESA Multi-Omics (HHSN2682015000031/HSN26800004). The MESA projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for the Multi-Ethnic Study of Atherosclerosis (MESA) projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491, and R01HL105756. The Three City (3C) Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” Ilana Caro received a grant from the EUR digital public health. This PhD program is supported within the framework of the PIA3 (Investment for the future). Project reference 17-EURE-0019.
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Affiliation(s)
- Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Alison E Fohner
- Department of Epidemiology, University of Washington, Seattle, WA, USA.
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Dan Liu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ilana Caro
- University of Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux Population Health Research Center, UMR 1219, CHU Bordeaux, Bordeaux, France
| | - Joni V Lindbohm
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, The Klarman Cell Observatory, Cambridge, MA, USA
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Osorio Meirelles
- National Institute on Aging, National Institutes of Health, Laboratory of Epidemiology and Population Science, Bethesda, MD, USA
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Valborg Gudmundsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Adele M Taylor
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Albert Henry
- Institute of Cardiovascular Science, University of London, London, UK
| | - Alexa S Beiser
- Department of Biostatistics, Boston University, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Ali Shojaie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Annabell Coors
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Annette L Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Departments of Family Medicine, University of Washington, Seattle, WA, USA
| | - Claudia Langenberg
- Precision Healthcare Institute, Queen Mary University of London, London, UK
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Claudia L Satizabal
- Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences and Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eleanor Wheeler
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | | | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Julián Candia
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, USA
| | - Maik Pietzner
- Precision Healthcare Institute, Queen Mary University of London, London, UK
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Oscar L Lopez
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Robert E Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Thomas R Austin
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Timothy M Hughes
- Department of Internal Medicine, Section of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Valur Emilsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Ramachandran S Vasan
- Framingham Heart Study, Framingham, MA, USA
- University of Texas School of Public Health in San Antonio, San Antonio, TX, USA
- University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yineng Zhu
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Christophe Tzourio
- University of Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux Population Health Research Center, UMR 1219, CHU Bordeaux, Bordeaux, France
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Mika Kivimäki
- UCL Brain Sciences, University College London, London, UK
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Stephanie Debette
- University of Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux Population Health Research Center, UMR 1219, CHU Bordeaux, Bordeaux, France
- Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M Psaty
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences and Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Myriam Fornage
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
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7
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Merchant RA, Chan YH, Anbarasan D, Aprahamian I. Association of Motoric Cognitive Risk Syndrome with Sarcopenia and Systemic Inflammation in Pre-Frail Older Adults. Brain Sci 2023; 13:936. [PMID: 37371414 DOI: 10.3390/brainsci13060936] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/04/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Motoric cognitive risk syndrome (MCR) is defined by the presence of slow gait and subjective cognitive decline. It is well recognized as a prodrome for dementia, but the biological mechanism and trajectory for MCR are still lacking. The objective of this study was to explore the association of MCR with body composition, including sarcopenia and systemic inflammation, in pre-frail older adults in a cross-sectional study of 397 pre-frail community-dwelling older adults. Data on demographics, physical function, frailty, cognition (Montreal Cognitive Assessment (MoCA)), perceived health and depression were collected. Body composition was measured using a bioelectrical impedance analyzer. Systemic inflammatory biomarkers, such as progranulin, growth differentiation factor-15 (GDF-15), interleukin-10 (IL-10), interleukin-6 and tumor necrosis factor-α (TNF-α), were collected. Univariate and multivariate logistic regression were used to analyze the association between MCR, body composition, sarcopenia and systemic inflammatory biomarkers. The prevalence of MCR was 14.9%. They were significantly older and there were more females, depression, functional impairment, lower education, physical activity and MoCA scores. Body fat percentage (BF%), fat mass index, fat to fat free mass ratio (FM/FFM) and sarcopenia prevalence were significantly higher in MCR. Serum GDF-15 and TNF-α levels were highest with progranulin/TNF-α and IL-10/TNF-α ratio lowest in MCR. Compared to healthy patients, MCR was significantly associated with sarcopenia (aOR 2.62; 95% CI 1.46-3.17), BF% (aOR 1.06; 95% CI 1.01-1.12), FMI (aOR 1.16; 95% CI 1.02-1.30) and FM/FFM (aOR 6.38; 95% CI 1.20-33.98). The association of IL-10 to TNF-α ratio (aOR 0.98, 95% CI 0.97-0.99) and IL-10 (aOR 2.22, 95% CI 0.05-0.98) with MCR were independent of sarcopenia and BF%. Longitudinal population studies are needed to understand the role of body fat indices and IL-10 in pre-frail older adults with MCR and trajectory to dementia.
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Affiliation(s)
- Reshma Aziz Merchant
- Division of Geriatric Medicine, Department of Medicine, National University Hospital, 1E Kent Ridge Road, Singapore 119228, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
| | - Denishkrshna Anbarasan
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Ivan Aprahamian
- Geriatrics Division, Department of Internal Medicine, Jundiai Medical School, Jundiai 13202-550, SP, Brazil
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8
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Katabathula S, Davis PB, Xu R. Comorbidity-driven multi-modal subtype analysis in mild cognitive impairment of Alzheimer's disease. Alzheimers Dement 2023; 19:1428-1439. [PMID: 36166485 PMCID: PMC10040466 DOI: 10.1002/alz.12792] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND Mild cognitive impairment (MCI) is a heterogeneous condition with high individual variabilities in clinical outcomes driven by patient demographics, genetics, brain structure features, blood biomarkers, and comorbidities. Multi-modality data-driven approaches have been used to discover MCI subtypes; however, disease comorbidities have not been included as a modality though multiple diseases including hypertension are well-known risk factors for Alzheimer's disease (AD). The aim of this study was to examine MCI heterogeneity in the context of AD-related comorbidities along with other AD-relevant features and biomarkers. METHODS A total of 325 MCI subjects with 32 AD-relevant comorbidities and features were considered. Mixed-data clustering is applied to discover and compare MCI subtypes with and without including AD-related comorbidities. Finally, the relevance of each comorbidity-driven subtype was determined by examining their MCI to AD disease prognosis, descriptive statistics, and conversion rates. RESULTS We identified four (five) MCI subtypes: poor-, average-, good-, and best-AD prognosis by including comorbidities (without including comorbidities). We demonstrated that comorbidity-driven MCI subtypes differed from those identified without comorbidity information. We further demonstrated the clinical relevance of comorbidity-driven MCI subtypes. Among the four comorbidity-driven MCI subtypes there were substantial differences in the proportions of participants who reverted to normal function, remained stable, or converted to AD. The groups showed different behaviors, having significantly different MCI to AD prognosis, significantly different means for cognitive test-related and plasma features, and by the proportion of comorbidities. CONCLUSIONS Our study indicates that AD comorbidities should be considered along with other diverse AD-relevant characteristics to better understand MCI heterogeneity.
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Affiliation(s)
- Sreevani Katabathula
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Pamela B Davis
- Center for Community Health Integration, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
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9
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Gorenflo MP, Davis PB, Kendall EK, Olaker VR, Kaelber DC, Xu R. Association of Aspirin Use with Reduced Risk of Developing Alzheimer's Disease in Elderly Ischemic Stroke Patients: A Retrospective Cohort Study. J Alzheimers Dis 2023; 91:697-704. [PMID: 36502331 DOI: 10.3233/jad-220901] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Currently there are no effective therapies to prevent or halt the development of Alzheimer's disease (AD). Multiple risk factors are involved in AD, including ischemic stroke (IS). Aspirin is often prescribed following IS to prevent blood clot formation. Observational studies have shown inconsistent findings with respect to the relationship between aspirin use and the risk of AD. OBJECTIVE To investigate the relationship between aspirin therapy after IS and the new diagnosis of AD in elderly patients. METHODS This retrospective cohort study leveraged a large database that contains over 90 million electronic health records to compare the hazard rates of AD after IS in elderly patients prescribed aspirin versus those not prescribed aspirin after propensity-score matching for relevant confounders. RESULTS At 1, 3, and 5 years after first IS, elderly patients prescribed aspirin were less likely to develop AD than those not prescribed aspirin: Hazard Ratio = 0.78 [0.65,0.94], 0.81 [0.70,0.94], and 0.76 [0.70,0.92]. CONCLUSION Our findings suggest that aspirin use may prevent AD in patients with IS, a subpopulation at high risk of developing the disease.
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Affiliation(s)
- Maria P Gorenflo
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Pamela B Davis
- Center for Community Health Integration, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Ellen K Kendall
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Veronica R Olaker
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - David C Kaelber
- The Center for Clinical Informatics Research and Education, The MetroHealth System, Cleveland, OH, USA
| | - Rong Xu
- Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
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10
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Ding Q, Lamberts J, Konieczny AM, Bringedahl TB, Torres Garcia KY. Association of Autoimmune Disorders and Disease-modifying Antirheumatic Drugs: (DMARDs) with the Risk of Alzheimer's and/or Dementia: A Population Study Using Medicare Beneficiary Data. Curr Alzheimer Res 2023; 20:725-737. [PMID: 38288824 DOI: 10.2174/0115672050289966240110041616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 12/26/2023] [Accepted: 01/02/2024] [Indexed: 04/04/2024]
Abstract
OBJECTIVES Alzheimer's disease (AD) and/or dementia is a prevalent neurocognitive disorder primarily affecting individuals over the age of 65. Identifying specific causes of AD and/or dementia can be challenging, with emerging evidence suggesting a potential association with autoimmune inflammatory conditions such as rheumatoid arthritis (RA). This study aimed to assess the prevalence rate of AD and/or dementia among Medicare beneficiaries reporting an autoimmune disorder. Additionally, this study sought to identify the comparative prevalence of AD and/or dementia in patients with an autoimmune disorder who were using disease-modifying antirheumatic drugs (DMARDs) compared to those not using DMARDs. METHODS Cross-sectional secondary data analyses were conducted on Medicare Current Beneficiary Survey (MCBS) data from 2017 and 2018. The MCBS data consists of a nationally representative sample of the Medicare population, a population that is largely 65 and older, and provides de-identified patient information. Patients from this dataset with a self-reported autoimmune disorder were included in the analyses. Descriptive analyses were conducted on demographic variables, chronic conditions, and medication use. The prevalence of AD and/or dementia was compared between patients with and without an autoimmune disorder. A backward stepwise selection regression was used to identify the risk factors associated with the prevalence of AD and/or dementia. RESULTS The study included 18,929 Medicare beneficiaries, with 4,405 identified as having one autoimmune disorder. The prevalence of AD and/or dementia was significantly higher in patients with an autoimmune disorder. The multivariate regression showed that RA was significantly associated with a higher risk of AD and/or dementia. Other demographic factors, including advanced age, African-American or Hispanic ethnicity, low body mass index, and chronic conditions of ischemic heart disease, history of myocardial infarction, history of stroke, depression, mental health disorder(s), and traumatic brain injury also showed statistically significant associations with AD and/or dementia. Patients using DMARDs demonstrated a reduced likelihood of having AD and/or dementia, compared to patients not using DMARDs. CONCLUSION This study provides evidence of an association between RA and increased risk of AD and/or dementia. The findings suggest that DMARD use may have a protective effect against the development of AD and/or dementia in patients with an autoimmune disorder.
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Affiliation(s)
- Qian Ding
- Ferris State University College of Pharmacy, 220 Ferris Drive, Big Rapids, MI 49307, USA
| | - Jennifer Lamberts
- Ferris State University College of Pharmacy, 220 Ferris Drive, Big Rapids, MI 49307, USA
| | - Alison M Konieczny
- Ferris Library for Information, Technology, and Education, Big Rapids, MI 49307, USA
| | - Tyler B Bringedahl
- Trinity Health Muskegon, 1500 East Sherman Blvd., Muskegon, MI 49444, USA
| | - Kiara Y Torres Garcia
- St. Joseph Health System Family Medicine Center, 611 E Douglas Rd., Mishawaka, IN 46545, USA
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