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Adamowicz DH, Wu TC, Daly R, Irwin MR, Jeste DV, Tu XM, Eyler LT, Lee EE. Executive functioning trajectories and their prospective association with inflammatory biomarkers in schizophrenia and non-psychiatric comparison participants. Prog Neuropsychopharmacol Biol Psychiatry 2024; 128:110866. [PMID: 37742747 PMCID: PMC10829566 DOI: 10.1016/j.pnpbp.2023.110866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 09/11/2023] [Accepted: 09/20/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND AND HYPOTHESIS Cognitive change in people with schizophrenia (PwS) is challenging to assess, but important to understand. Previous studies with limited age ranges and follow-up were subject to practice effects. Controlling for practice effects in a well-established cohort, we examined executive functioning trajectories and their association with inflammatory biomarkers, hypothesizing that PwS will have worsening executive functioning over time compared to non-psychiatric comparison participants (NCs), predicted by higher baseline inflammation with a stronger relationship in PwS than NCs. STUDY DESIGN Executive functioning was assessed in 350 participants (n = 186 PwS, 164 NCs) at 12-16-month intervals (0 to 7 follow-up visits). Inflammatory biomarkers at baseline included high sensitivity C-Reactive Protein (hs-CRP), Interferon-gamma, Tumor Necrosis Factor (TNF)-alpha, and Interleukin(IL)-6, -8, and - 10. Executive functioning trajectories across diagnostic groups were estimated using a linear mixed-effects model controlling for age, sex, race/ethnicity, and education level, with additional models to assess prediction by baseline inflammation. STUDY RESULTS Over 4.4 years average follow-up, improvements in executive functioning were attenuated in PwS and older participants. Controlling for practice effects negated improvements, revealing declines among highly educated participants regardless of diagnosis. Higher baseline hs-CRP predicted worse executive functioning only among NCs, while TNF-alpha was predictive of change in all participants only after controlling for practice effects. Only the main effect of hs-CRP on executive function was significant after adjusting for multiple comparisons. None of the other inflammatory biomarkers predicted executive functioning or trajectories of performance among study participants. CONCLUSIONS Systemic inflammation as reflected by baseline inflammatory biomarker levels did not predict longitudinal declines in executive functioning. Additional studies examining the temporal dynamics of inflammation and cognition in PwS will help further clarify their relationship and associated mechanisms.
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Affiliation(s)
- David H Adamowicz
- Mass General Brigham, Department of Psychiatry, Division of Geriatric Psychiatry, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA 02115, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.
| | - Tsung-Chin Wu
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.
| | - Rebecca Daly
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, CA 92093, USA.
| | - Michael R Irwin
- Cousins Center for Psychoneuroimmunology, Semel Institute for Neuroscience, University of California, Los Angeles, CA, USA.
| | - Dilip V Jeste
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA.
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, CA 92093, USA; Desert-Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA.
| | - Ellen E Lee
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, CA 92093, USA; Desert-Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA.
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Gillespie NA, Elman JA, McKenzie RE, Tu XM, Xian H, Reynolds CA, Panizzon MS, Lyons MJ, Eglit GML, Neale MC, Rissman RA, Franz C, Kremen WS. The heritability of blood-based biomarkers related to risk of Alzheimer's disease in a population-based sample of early old-age men. Alzheimers Dement 2024; 20:356-365. [PMID: 37622539 PMCID: PMC10843753 DOI: 10.1002/alz.13407] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 08/26/2023]
Abstract
INTRODUCTION Despite their increased application, the heritability of Alzheimer's disease (AD)-related blood-based biomarkers remains unexplored. METHODS Plasma amyloid beta 40 (Aβ40), Aβ42, the Aβ42/40 ratio, total tau (t-tau), and neurofilament light (NfL) data came from 1035 men 60 to 73 years of age (μ = 67.0, SD = 2.6). Twin models were used to calculate heritability and the genetic and environmental correlations between them. RESULTS Additive genetics explained 44% to 52% of Aβ42, Aβ40, t-tau, and NfL. The Aβ42/40 ratio was not heritable. Aβ40 and Aβ42 were genetically near identical (rg = 0.94). Both Aβ40 and Aβ42 were genetically correlated with NfL (rg = 0.35 to 0.38), but genetically unrelated to t-tau. DISCUSSION Except for Aβ42/40, plasma biomarkers are heritable. Aβ40 and Aβ42 share mostly the same genetic influences, whereas genetic influences on plasma t-tau and NfL are largely unique in early old-age men. The absence of genetic associations between the Aβs and t-tau is not consistent with the amyloid cascade hypothesis.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behaviour GeneticsDepartment of PsychiatryVirginia Commonwealth UniversityRichmondVirginiaUSA
- QIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Jeremy A. Elman
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Ruth E. McKenzie
- Department of PsychologyBoston UniversityBostonMassachusettsUSA
- School of Education and Social PolicyMerrimack CollegeNorth AndoverMassachusettsUSA
| | - Xin M. Tu
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
- Department of Family Medicine and Public HealthUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Hong Xian
- Department of Epidemiology and BiostatisticsSaint. Louis UniversitySt. LouisMissouriUSA
- Research Service, VA St. Louis Healthcare SystemSt. LouisMissouriUSA
| | | | - Matthew S. Panizzon
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Michael J. Lyons
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
| | - Graham M. L. Eglit
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behaviour GeneticsDepartment of PsychiatryVirginia Commonwealth UniversityRichmondVirginiaUSA
| | - Robert A. Rissman
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Carol Franz
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - William S. Kremen
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
- Department of NeurosciencesUniversity of California, San DiegoLa JollaCaliforniaUSA
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Chronister BNC, Yang K, Yang AR, Lin T, Tu XM, Lopez-Paredes D, Checkoway H, Suarez-Torres J, Gahagan S, Martinez D, Barr D, Moore RC, Suarez-Lopez JR. Erratum: "Urinary Glyphosate, 2,4-D and DEET Biomarkers in Relation to Neurobehavioral Performance in Ecuadorian Adolescents in the ESPINA Cohort". Environ Health Perspect 2023; 131:129001. [PMID: 38060260 DOI: 10.1289/ehp14201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
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Chronister BN, Yang K, Yang AR, Lin T, Tu XM, Lopez-Paredes D, Checkoway H, Suarez-Torres J, Gahagan S, Martinez D, Barr D, Moore RC, Suarez-Lopez JR. Urinary Glyphosate, 2,4-D and DEET Biomarkers in Relation to Neurobehavioral Performance in Ecuadorian Adolescents in the ESPINA Cohort. Environ Health Perspect 2023; 131:107007. [PMID: 37819080 PMCID: PMC10566341 DOI: 10.1289/ehp11383] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 08/22/2023] [Accepted: 08/30/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND Herbicides are the most used class of pesticides worldwide, and insect repellents are widely used globally. Yet, there is a dearth of studies characterizing the associations between these chemical groups and human neurobehavior. Experimental studies suggest that glyphosate and 2,4-dichlorophenoxyacetic acid (2,4-D) herbicides can affect neurobehavior and the cholinergic and glutamatergic pathways in the brain. We aim to assess whether herbicides and insect repellents are associated with neurobehavioral performance in adolescents. METHODS We assessed 519 participants (11-17 years of age) living in agricultural communities in Ecuador. We quantified urinary concentrations of glyphosate, 2,4-D, and two N,N-diethyl-meta-toluamide (DEET) insect repellent metabolites [3-(diethylcarbamoyl)benzoic acid (DCBA) and 3-(ethylcarbamoyl)benzoic acid (ECBA)] using isotope-dilution mass spectrometry. We assessed neurobehavioral performance using 9 subtests across 5 domains (attention/inhibitory control, memory/learning, language, visuospatial processing, and social perception). We characterized the associations using generalized estimating equations and multiple imputation for metabolites below detection limits. Models were adjusted for demographic and anthropometric characteristics, urinary creatinine, and sexual maturation. Mediation by salivary cortisol, dehydroepiandrosterone, 17 β -estradiol , and testosterone was assessed using structural equation modeling. RESULTS The mean of each neurobehavioral domain score was between 7.0 and 8.7 [standard deviation (SD) range: 2.0-2.3]. Glyphosate was detected in 98.3% of participants, 2,4-D in 66.2%, DCBA in 63.3%, and ECBA in 33.4%. 2,4-D was negatively associated with all neurobehavioral domains, but statistically significant associations were observed with attention/inhibition [score difference per 50% higher metabolite concentration ( β ) = - 0.19 95% confidence interval (CI): - 0.31 , - 0.07 ], language [β = - 0.12 (95% CI: - 0.23 , - 0.01 )], and memory/learning [β = - 0.11 (95% CI: - 0.22 , 0.01)]. Glyphosate had a statistically significant negative association only with social perception [β = - 0.08 (95% CI: - 0.14 , - 0.01 )]. DEET metabolites were not associated with neurobehavioral performance. Mediation by gender and adrenal hormones was not observed. CONCLUSION This study describes worse neurobehavioral performance associated with herbicide exposures in adolescents, particularly with 2,4-D. Replication of these findings among other pediatric and adult populations is needed. https://doi.org/10.1289/EHP11383.
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Affiliation(s)
- Briana N.C. Chronister
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
- School of Public Health, San Diego State University, San Diego, California, USA
| | - Kun Yang
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
| | - Audrey R. Yang
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
| | - Tuo Lin
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
| | - Xin M. Tu
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
| | | | - Harvey Checkoway
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
| | | | - Sheila Gahagan
- Department of Pediatrics, University of California San Diego, San Diego, California, USA
| | | | - Dana Barr
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Raeanne C. Moore
- Department of Psychiatry, University of California San Diego, San Diego, California, USA
| | - Jose R. Suarez-Lopez
- The Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California, USA
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Thomas ML, Palmer BW, Lee EE, Liu J, Daly R, Tu XM, Jeste DV. Abbreviated San Diego Wisdom Scale (SD-WISE-7) and Jeste-Thomas Wisdom Index (JTWI) - CORRIGENDUM. Int Psychogeriatr 2023; 35:587. [PMID: 35319427 PMCID: PMC10938455 DOI: 10.1017/s1041610222000011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Kolaja CA, Belding JN, Boparai SK, Castañeda SF, Geronimo-Hara TR, Powell TM, Tu XM, Walstrom JL, Sheppard BD, Rull RP. Survey response over 15 years of follow-up in the Millennium Cohort Study. BMC Med Res Methodol 2023; 23:205. [PMID: 37689640 PMCID: PMC10492282 DOI: 10.1186/s12874-023-02018-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 08/09/2023] [Indexed: 09/11/2023] Open
Abstract
BACKGROUND Patterns of survey response and the characteristics associated with response over time in longitudinal studies are important to discern for the development of tailored retention efforts aimed at minimizing response bias. The Millennium Cohort Study, the largest and longest running cohort study of military personnel and veterans, is designed to examine the long-term health effects of military service and experiences and thus relies on continued participant survey responses over time. Here, we describe the response rates for follow-up survey data collected over 15 years and identify characteristics associated with follow-up survey response and mode of response (paper vs. web). METHOD Patterns of follow-up survey response and response mode (web, paper, none) were examined among eligible participants (n=198,833), who were initially recruited in four panels from 2001 to 2013 in the Millennium Cohort Study, for a follow-up period of 3-15 years (2004-2016). Military and sociodemographic factors (i.e., enrollment panel, sex, birth year, race and ethnicity, educational attainment, marital status, service component, service branch, pay grade, military occupation, length of service, and time deployed), life experiences and health-related factors (i.e., military deployment/combat experience, life stressors, mental health, physical health, and unhealthy behaviors) were used to examine follow-up response and survey mode over time in multivariable generalized estimating equation models. RESULTS Overall, an average response rate of 60% was observed across all follow-up waves. Factors associated with follow-up survey response over time included increased educational attainment, married status, female sex, older age, military deployment (regardless of combat experience), and higher number of life stressors, mental health issues, and physical health diagnoses. CONCLUSION Despite the challenges associated with collecting multiple waves of follow-up survey data from members of the U.S. military during and after service, the Millennium Cohort Study has maintained a relatively robust response rate over time. The incorporation of tailored messages and outreach to those groups least likely to respond over time may improve retention and thereby increase the representativeness and generalizability of collected survey data.
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Affiliation(s)
- Claire A Kolaja
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA.
- Leidos, Inc, San Diego, CA, USA.
| | - Jennifer N Belding
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
| | - Satbir K Boparai
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Sheila F Castañeda
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
| | - Toni Rose Geronimo-Hara
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Teresa M Powell
- Leidos, Inc, San Diego, CA, USA
- Army Resilience Directorate, Headquarters United States Department of the Army, Deputy Chief of Staff G-1, Arlington, VA, USA
| | - Xin M Tu
- Clinical and Translational Research Institute, University of California San Diego, San Diego, CA, USA
| | - Jennifer L Walstrom
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Beverly D Sheppard
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
- Leidos, Inc, San Diego, CA, USA
| | - Rudolph P Rull
- Deployment Health Research Department, Naval Health Research Center, San Diego, CA, USA
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Chopyk J, Cobián Güemes AG, Ramirez-Sanchez C, Attai H, Ly M, Jones MB, Liu R, Liu C, Yang K, Tu XM, Abeles SR, Nelson K, Pride DT. Common antibiotics, azithromycin and amoxicillin, affect gut metagenomics within a household. BMC Microbiol 2023; 23:206. [PMID: 37528343 PMCID: PMC10394940 DOI: 10.1186/s12866-023-02949-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/19/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND The microbiome of the human gut serves a role in a number of physiological processes, but can be altered through effects of age, diet, and disturbances such as antibiotics. Several studies have demonstrated that commonly used antibiotics can have sustained impacts on the diversity and the composition of the gut microbiome. The impact of the two most overused antibiotics, azithromycin, and amoxicillin, in the human microbiome has not been thoroughly described. In this study, we recruited a group of individuals and unrelated controls to decipher the effects of the commonly used antibiotics amoxicillin and azithromycin on their gut microbiomes. RESULTS We characterized the gut microbiomes by metagenomic sequencing followed by characterization of the resulting microbial communities. We found that there were clear and sustained effects of the antibiotics on the gut microbial community with significant alterations in the representations of Bifidobacterium species in response to azithromycin (macrolide antibiotic). These results were supported by significant increases identified in putative antibiotic resistance genes associated with macrolide resistance. Importantly, we did not identify these trends in the unrelated control individuals. There were no significant changes observed in other members of the microbial community. CONCLUSIONS As we continue to focus on the role that the gut microbiome plays and how disturbances induced by antibiotics might affect our overall health, elucidating members of the community most affected by their use is of critical importance to understanding the impacts of common antibiotics on those who take them. Clinical Trial Registration Number NCT05169255. This trial was retrospectively registered on 23-12-2021.
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Affiliation(s)
- Jessica Chopyk
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA
| | - Ana Georgina Cobián Güemes
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA
| | | | - Hedieh Attai
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA
| | - Melissa Ly
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA
| | - Marcus B Jones
- Genomic Medicine, J. Craig Venter Institute, La Jolla, CA, 92037, USA
| | - Roland Liu
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA
| | - Chenyu Liu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, 92093, USA
| | - Kun Yang
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, 92093, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, 92093, USA
| | - Shira R Abeles
- Department of Medicine, University of California San Diego, San Diego, CA, 92093, USA
| | - Karen Nelson
- Genomic Medicine, J. Craig Venter Institute, La Jolla, CA, 92037, USA
| | - David T Pride
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, MC 0612, La Jolla, San Diego, CA, 92093-0612, USA.
- Department of Medicine, University of California San Diego, San Diego, CA, 92093, USA.
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Sanderson-Cimino M, Chen R, Tu XM, Elman JA, Jak AJ, Kremen WS. Misinterpreting cognitive change over multiple timepoints: When practice effects meet age-related decline. Neuropsychology 2023; 37:568-581. [PMID: 37079809 PMCID: PMC10313772 DOI: 10.1037/neu0000903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
OBJECTIVE Practice effects (PE) on cognitive testing have been shown to delay detection of impairment and impede our ability to assess change. When decline over time is expected, as with older adults or progressive diseases, failure to adequately address PEs may lead to inaccurate conclusions because PEs artificially boost scores while pathology- or age-related decline reduces scores. Unlike most methods, a participant-replacement approach can separate pathology- or age-related decline from PEs; however, this approach has only been used across two timepoints. More than two timepoints make it possible to determine if PEs level out after the first follow-up, but it is analytically challenging because individuals may not be assessed at every timepoint. METHOD We examined 1,190 older adults who were cognitively unimpaired (n = 809) or had mild cognitive impairment (MCI; n = 381). Participants completed six neuropsychological measures at three timepoints (baseline, 12-month, 24-month). We implemented a participant-replacement method using generalized estimating equations in comparisons of matched returnees and replacements to calculate PEs. RESULTS Without accounting for PEs, cognitive function appeared to improve or stay the same. However, with the participant-replacement method, we observed significant PEs within both groups at all timepoints. PEs did not uniformly decrease across time; some-specifically on episodic memory measures-continued to increase beyond the first follow-up. CONCLUSION A replacement method of PE adjustment revealed significant PEs across two follow-ups. As expected in these older adults, accounting for PEs revealed cognitive decline. This, in turn, means earlier detection of cognitive deficits, including progression to MCI, and more accurate characterization of longitudinal change. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Mark Sanderson-Cimino
- Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Center for Behavior Genetics of Aging, University of California, San Diego
| | - Ruohui Chen
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego
| | - Xin M. Tu
- School of Medicine, University of California, San Diego
- Family Medicine and Public Health, University of California San Diego
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California, San Diego
- School of Medicine, University of California, San Diego
| | - Amy J. Jak
- Center for Behavior Genetics of Aging, University of California, San Diego
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California, San Diego
- School of Medicine, University of California, San Diego
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Liu A, He H, Tu XM, Tang W. On testing proportional odds assumptions for proportional odds models. Gen Psychiatr 2023; 36:e101048. [PMID: 37565234 PMCID: PMC10410795 DOI: 10.1136/gpsych-2023-101048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 06/06/2023] [Indexed: 08/12/2023] Open
Abstract
Proportional odds models are commonly used to model ordinal responses, but the proportional odds assumption may not hold in practice, leading to biased inference. Tests such as score, Wald and likelihood ratio (LR) have been proposed to evaluate the proportional odds assumption based on models without the assumption. Brant has proposed an independent binary model-based Wald-type test, and Wolfe and Gould have extended the idea to propose an LR-type test. This paper provides a brief review of the Brant and Wolfe-Gould tests for evaluating the proportional odds assumption and evaluates their performance through simulation studies and a real data example. Sample programs are provided in SAS, SPSS and Stata to facilitate the implementation of these tests using standard statistical software packages. This study highlights the importance of evaluating the proportional odds assumption when using proportional odds models for ordinal responses. The sample programs provided in this paper make it easy for researchers to apply these tests in their own analyses using standard statistical software packages.
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Affiliation(s)
- Anqi Liu
- Department of Biostatistics and Data Science, Tulane University, New Orleans, Louisiana, USA
| | - Hua He
- Department of Epidemiology, Tulane University, New Orleans, Louisiana, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Wan Tang
- Department of Biostatistics and Data Science, Tulane University, New Orleans, Louisiana, USA
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Garduno AC, Laughlin GA, Bergstrom J, Tu XM, Cummins KM, Franz CE, Elman JA, Lyons MJ, Reynolds CA, Neale MC, Gillespie NA, Xian H, McKenzie RE, Toomey R, Kremen WS, Panizzon MS, McEvoy LK. Alcohol use and cognitive aging in middle-aged men: The Vietnam Era Twin Study of Aging. J Int Neuropsychol Soc 2023; 29:235-245. [PMID: 35465863 PMCID: PMC9592679 DOI: 10.1017/s1355617722000169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To determine associations of alcohol use with cognitive aging among middle-aged men. METHOD 1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003-2007 to 2016-2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1-4 drinks in past 14 days), light (5-14 drinks), moderate (15-28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors. RESULTS Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by -0.21 SD (95% CI -0.35, -0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, -0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association. CONCLUSIONS Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly.
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Affiliation(s)
- Alexis C Garduno
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Gail A Laughlin
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Jaclyn Bergstrom
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Xin M Tu
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Kevin M Cummins
- Department of Public Health, California State University, Fullerton, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hong Xian
- Department of Statistics, St Louis University, St Louis, MO, USA
- Research Service, VA St Louis Healthcare System, St Louis, MO, USA
| | - Ruth E McKenzie
- Department of Psychology, Boston University, Boston, MA, USA
- Department of Applied Human Development and Community Studies, Merrimack College, North Andover, MA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Linda K McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
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11
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Borin JM, Liu R, Wang Y, Wu TC, Chopyk J, Huang L, Kuo P, Ghose C, Meyer JR, Tu XM, Schnabl B, Pride DT. Fecal virome transplantation is sufficient to alter fecal microbiota and drive lean and obese body phenotypes in mice. bioRxiv 2023:2023.02.03.527064. [PMID: 36778328 PMCID: PMC9915734 DOI: 10.1101/2023.02.03.527064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background The gastrointestinal microbiome plays a significant role in numerous host processes and has an especially large impact on modulating the host metabolism. Prior studies have shown that when mice receive fecal transplants from obese donors that were fed high-fat diets (HFD) (even when recipient mice are fed normal diets after transplantation), they develop obese phenotypes. These studies demonstrate the prominent role that the gut microbiota play in determining lean and obese phenotypes. While much of the credit has been given to gut bacteria, studies have not measured the impact of gut viruses on these phenotypes. To address this shortcoming, we gavaged mice with viromes isolated from donors fed HFD or normal chow. By characterizing the mice’s gut bacterial biota and weight-gain phenotypes over time, we demonstrate that viruses can shape the gut bacterial community and affect weight gain or loss. Results We gavaged mice longitudinally over 4 weeks while measuring their body weights and collecting fecal samples for 16S rRNA amplicon sequencing. We evaluated mice that were fed normal chow or high-fat diets, and gavaged each group with either chow-derived fecal viromes, HFD-derived fecal viromes, or phosphate buffered saline controls. We found a significant effect of gavage type, where mice fed chow but gavaged with HFD-derived viromes gained significantly more weight than their counterparts receiving chow-derived viromes. The converse was also true: mice fed HFD but gavaged with chow-derived viromes gained significantly less weight than their counterparts receiving HFD-derived viromes. These results were replicated in two separate experiments and the phenotypic changes were accompanied by significant and identifiable differences in the fecal bacterial biota. Notably, there were differences in Lachnospirales and Clostridia in mice fed chow but gavaged with HFD-derived fecal viromes, and in Peptostreptococcales, Oscillospirales, and Lachnospirales in mice fed HFD but gavaged with chow-derived fecal viromes. Due to methodological limitations, we were unable to identify specific bacterial species or strains that were responsible for respective phenotypic changes. Conclusions This study confirms that virome-mediated perturbations can alter the fecal microbiome in an in vivo model and indicates that such perturbations are sufficient to drive lean and obese phenotypes in mice.
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Affiliation(s)
- Joshua M Borin
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Roland Liu
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Yanhan Wang
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Tsung-Chin Wu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Jessica Chopyk
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Lina Huang
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Peiting Kuo
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | | | - Justin R Meyer
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Bernd Schnabl
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - David T Pride
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
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12
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Grunvald E, Wei J, Lin T, Yang K, Tu XM, Lunde O, Ross E, Cheng J, DeConde J, Farber N. Exploring the Effect of Adding an Interactive Lecture to a Standardized Patient Curriculum on the Attitudes of Third-Year Medical Students About Patients With Obesity: A Quasi-Experimental Study. J Med Educ Curric Dev 2023; 10:23821205231207683. [PMID: 37854280 PMCID: PMC10580723 DOI: 10.1177/23821205231207683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/13/2023] [Indexed: 10/20/2023]
Abstract
OBJECTIVES Anti-obesity bias is pervasive among medical professionals, students, and trainees. Stigmatization of patients leads to suboptimal care and clinical outcomes. Educational strategies in medical training are needed to reverse these attitudes. The aim of this study was to evaluate the effect of an innovative didactic intervention and a standardized patient (SP) exercise on attitudes towards patients with obesity among medical students. METHODS In 2016, a quasi-experimental study design was used at a US medical school. The class was divided into 2 groups according to a pre-determined protocol based on their clinical schedule, one assessed after exposure to a SP group and the other after exposure to the SP and an interactive lecture (IL + SP group) with real patients. The Attitudes about Treating Patients with Obesity and The Perceived Causes of Obesity questionnaires measured changes in several domains. A generalized estimating equations model was used to estimate the effect of the interventions both within and between groups. RESULTS Both groups showed improvements in negative and positive attitudes, although the reduction in scores for the negative attitude domain did not reach statistical significance in the IL + SP group (for the SP group, P = .01 and < .001, respectively; for the IL + SP group, P = .15 and .01, respectively). For perceived causes of obesity, there were no statistically significant changes for pre-post survey measures within each group, except for the physiologic causes domain in the SP group (P = .03). The addition of an IL to a SP curriculum did not result in any changes for any domain in between-group analyses. CONCLUSIONS Although adding a novel intervention utilizing real patients to a SP curriculum failed to show an additional educational benefit, our study showed that it is possible to influence attitudes of medical students regarding patients with obesity.
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Affiliation(s)
- Eduardo Grunvald
- University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Jennie Wei
- University of California San Diego School of Medicine, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, La Jolla, CA, USA
| | - Tuo Lin
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Kun Yang
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Xin M Tu
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Ottar Lunde
- University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Evelyn Ross
- University of California San Diego School of Medicine, La Jolla, CA, USA
- Fox Chase Cancer Center, Temple University, Philadelphia, PA, USA
| | - Jessica Cheng
- University of California San Diego School of Medicine, La Jolla, CA, USA
- Elica Health Centers, West Sacramento, CA, USA
| | - Jennifer DeConde
- University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Neil Farber
- University of California San Diego School of Medicine, La Jolla, CA, USA
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13
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Franz CE, Gustavson DE, Elman JA, Fennema-Notestine C, Hagler DJ, Baraff A, Tu XM, Wu TC, DeAnda J, Beck A, Kaufman JD, Whitsel N, Finch CE, Chen JC, Lyons MJ, Kremen WS. Associations Between Ambient Air Pollution and Cognitive Abilities from Midlife to Early Old Age: Modification by APOE Genotype. J Alzheimers Dis 2023; 93:193-209. [PMID: 36970897 PMCID: PMC10827529 DOI: 10.3233/jad-221054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) measures of ambient air pollution are associated with accelerated age-related cognitive impairment, and Alzheimer's disease and related dementias (ADRD). OBJECTIVE We examined associations between air pollution, four cognitive factors, and the moderating role of apolipoprotein E (APOE) genotype in the understudied period of midlife. METHODS Participants were ∼1,100 men in the Vietnam Era Twin Study of Aging. Baseline cognitive assessments were from 2003 to 2007. Measures included past (1993-1999) and recent (3 years prior to baseline assessment) PM2.5 and NO2 exposure, in-person assessment of episodic memory, executive function, verbal fluency, and processing speed, and APOE genotype. Average baseline age was 56 years with a 12-year follow-up. Analyses adjusted for health and lifestyle covariates. RESULTS Performance in all cognitive domains declined from age 56 to 68. Higher PM2.5 exposures were associated with worse general verbal fluency. We found significant exposure-by-APOE genotype interactions for specific cognitive domains: PM2.5 with executive function and NO2 with episodic memory. Higher PM2.5 exposure was related to worse executive function in APOE ɛ4 carriers, but not in non-carriers. There were no associations with processing speed. CONCLUSION These results indicate negative effects of ambient air pollution exposure on fluency alongside intriguing differential modifications of cognitive performance by APOE genotype. APOE ɛ4 carriers appeared more sensitive to environmental differences. The process by which air pollution and its interaction with genetic risk for ADRD affects risk for later life cognitive decline or progression to dementia may begin in midlife.
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Affiliation(s)
- Carol E. Franz
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Daniel E. Gustavson
- Institute for Behavior Genetics, University of Colorado Boulder, Boulder, CO
| | - Jeremy A. Elman
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
| | - Donald J. Hagler
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Aaron Baraff
- Vietnam Era Twin Registry, VA Puget Sound Health Care, Seattle, WA
| | - Xin M. Tu
- Herbert Wertheim School of Public Health & Human Longevity Science, University of California San Diego, CA
| | - Tsung-Chin Wu
- Herbert Wertheim School of Public Health & Human Longevity Science, University of California San Diego, CA
| | - Jaden DeAnda
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Psychology, San Diego State University, San Diego, CA
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle, WA
| | - Joel D. Kaufman
- Epidemiology, Environmental and Occupational Health Sciences, and General Internal Medicine, University of Washington, Seattle, WA
| | - Nathan Whitsel
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Caleb E. Finch
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA
| | - Jiu-Chiuan Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - William S. Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
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14
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Borin JM, Liu R, Wang Y, Wu TC, Chopyk J, Huang L, Kuo P, Ghose C, Meyer JR, Tu XM, Schnabl B, Pride DT. Fecal virome transplantation is sufficient to alter fecal microbiota and drive lean and obese body phenotypes in mice. Gut Microbes 2023; 15:2236750. [PMID: 37475473 PMCID: PMC10364654 DOI: 10.1080/19490976.2023.2236750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023] Open
Abstract
The gastrointestinal microbiome plays a significant role in modulating numerous host processes, including metabolism. Prior studies show that when mice receive fecal transplants from obese donors on high-fat diets (HFD) (even when recipient mice are fed normal diets after transplantation), they develop obese phenotypes, demonstrating the prominent role that gut microbiota play in determining lean and obese phenotypes. While much of the credit has been given to gut bacteria, the impact of gut viruses on these phenotypes is understudied. To address this shortcoming, we gavaged mice with viromes isolated from donors fed HFD or normal chow over a 4-week study. By characterizing the gut bacterial biota via 16S rRNA amplicon sequencing and measuring mouse weights over time, we demonstrate that transplanted viruses affect the gut bacterial community, as well as weight gain/loss. Notably, mice fed chow but gavaged with HFD-derived viromes gained more weight than their counterparts receiving chow-derived viromes. The converse was also true: mice fed HFD but gavaged with chow-derived viromes gained less weight than their counterparts receiving HFD-derived viromes. Results were replicated in two independent experiments and phenotypic changes were accompanied by significant and identifiable differences in the fecal bacterial biota. Due to methodological limitations, we were unable to identify the specific bacterial strains responsible for respective phenotypic changes. This study confirms that virome-mediated perturbations can alter the fecal microbiome in vivo and indicates that such perturbations are sufficient to drive lean and obese phenotypes in mice.
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Affiliation(s)
- Joshua M. Borin
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Roland Liu
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Yanhan Wang
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Tsung-Chin Wu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Jessica Chopyk
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Lina Huang
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Peiting Kuo
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | | | - Justin R. Meyer
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Xin M. Tu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Bernd Schnabl
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - David T. Pride
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
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15
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Lin T, Zhao R, Tu S, Wu H, Zhang H, Tu XM. On modelling relative risks for longitudinal binomial responses: implications from two dueling paradigms. Gen Psychiatr 2023; 36:e100977. [PMID: 36919082 PMCID: PMC10008153 DOI: 10.1136/gpsych-2022-100977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/10/2023] [Indexed: 03/16/2023] Open
Abstract
Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis. Indeed, since Zou published his modified Poisson regression approach for modelling RR for cross-sectional data, his paper has been cited over 7 000 times, demonstrating the popularity of this alternative measure of risk in regression analysis involving binary responses. As longitudinal studies have become increasingly popular in clinical trials and observational studies, it is imperative to extend Zou's approach for longitudinal data. The two most popular approaches for longitudinal data analysis are the generalised linear mixed-effects model (GLMM) and generalised estimating equations (GEE). However, the parametric GLMM cannot be used for the extension within the current context, because Zou's approach treats the binary response as a Poisson variable, which is at odds with the Bernoulli distribution for the binary response. On the other hand, as it imposes no mathematical model on data distributions, the semiparametric GEE is coherent with Zou's modified Poisson regression. In this paper, we develop a GEE-based longitudinal model for binary responses to provide inference about RR.
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Affiliation(s)
- Tuo Lin
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Rongzhe Zhao
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Shengjia Tu
- College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Hao Wu
- Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia, USA
| | - Hui Zhang
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
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16
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Kim BK, Tamaki N, Imajo K, Yoneda M, Sutter N, Jung J, Lin T, Tu XM, Bergstrom J, Nguyen K, Nguyen L, Le T, Madamba E, Richards L, Valasek MA, Behling C, Sirlin CB, Nakajima A, Loomba R. Head-to-head comparison between MEFIB, MAST, and FAST for detecting stage 2 fibrosis or higher among patients with NAFLD. J Hepatol 2022; 77:1482-1490. [PMID: 35973577 DOI: 10.1016/j.jhep.2022.07.020] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 06/29/2022] [Accepted: 07/23/2022] [Indexed: 12/11/2022]
Abstract
BACKGROUND & AIMS Patients with non-alcoholic fatty liver disease (NAFLD) and significant fibrosis (fibrosis stage ≥2) are candidates for pharmacological trials. The aim of this study was to perform a head-to-head comparison of the diagnostic test characteristics of three non-invasive stiffness-based models including MEFIB (magnetic resonance elastography [MRE] plus FIB-4), MAST (magnetic resonance imaging [MRI]-aspartate aminotransferase [AST]), and FAST (FibroScan-AST) for detecting significant fibrosis. METHODS This prospective study included 563 patients with biopsy-proven NAFLD undergoing contemporaneous MRE, MRI proton density fat fraction (MRI-PDFF) and FibroScan from two prospective cohorts derived from Southern California and Japan. Diagnostic performances of models were evaluated by area under the receiver-operating characteristic curve (AUC). RESULTS The mean age of the cohort was 56.5 years (51% were women). Significant fibrosis was observed in 51.2%. To detect significant fibrosis, MEFIB outperformed both MAST and FAST (both p <0.001); AUCs for MEFIB, MAST, and FAST were 0.901 (95% CI 0.875-0.928), 0.770 (95% CI 0.730-0.810), and 0.725 (95% CI 0.683-0.767), respectively. Using rule-in criteria, the positive predictive value of MEFIB (95.3%) was significantly higher than that of FAST (83.5%, p = 0.001) and numerically but not statistically greater than that of MAST (90.0%, p = 0.056). Notably, MEFIB's rule-in criteria covered more of the study population than MAST (34.1% vs. 26.6%; p = 0.006). Using rule-out criteria, the negative predictive value of MEFIB (90.1%) was significantly higher than that of either MAST (69.6%) or FAST (71.8%) (both p <0.001). Furthermore, to diagnose "at risk" non-alcoholic steatohepatitis defined as NAFLD activity score ≥4 and fibrosis stage ≥2, MEFIB outperformed both MAST and FAST (both p <0.05); AUCs for MEFIB, MAST, and FAST were 0.768 (95% CI 0.728-0.808), 0.719 (95% CI 0.671-0.766), and 0.687 (95% CI 0.640-0.733), respectively. CONCLUSIONS MEFIB was better than MAST and FAST for detection of significant fibrosis as well as "at risk" NASH. All three models provide utility for the risk stratification of NAFLD. LAY SUMMARY Non-alcoholic fatty liver disease (NAFLD) affects over 25% of the general population worldwide and is one of the main causes of chronic liver disease. Because so many individuals have NAFLD, it is not practical to perform liver biopsies to identify those with more severe disease who may require pharmacological interventions. Therefore, accurate non-invasive tests are crucial. Herein, we compared three such tests and found that a test called MEFIB was the best at detecting patients who might require treatment.
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Affiliation(s)
- Beom Kyung Kim
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States; Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Nobuharu Tamaki
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States; Department of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Tokyo, Japan
| | - Kento Imajo
- Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Kanagawa, Japan; Department of Gastroenterology, Shin-yurigaoka General Hospital, Kanagawa, Japan
| | - Masato Yoneda
- Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Kanagawa, Japan
| | - Nancy Sutter
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Jinho Jung
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Tuo Lin
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, United States
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, United States
| | - Jaclyn Bergstrom
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Khang Nguyen
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Leyna Nguyen
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Tracy Le
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Egbert Madamba
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Lisa Richards
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Mark A Valasek
- Department of Pathology, University of California San Diego, La Jolla, CA, United States
| | - Cynthia Behling
- Sharp Medical Group, Department of Pathology, University of California San Diego, La Jolla, CA, United States
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Atsushi Nakajima
- Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Kanagawa, Japan
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, United States; Division of Epidemiology, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, United States.
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17
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Franz CE, Elman JA, Fennema‐Notestine C, Whitsell N, Wu T, Tu XM, Qin YA, Kremen WS. APOE‐e4 Status Moderates Associations between Executive Function and Air Pollution Exposure in Older Men. Alzheimers Dement 2022. [DOI: 10.1002/alz.069339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | - Tsung‐Chin Wu
- University of California, San Diego San Diego CA USA
| | - Xin M Tu
- University of California, San Diego La Jolla CA USA
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18
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Panizzon MS, Deka R, Anglin T, Logue MW, Merritt V, Chang NN, Carter HK, Jasuja G, Lee K, Lynch J, Pagadala M, Rose B, Seibert T, Teerlink C, Tu XM, Hauger RL. Effects of Androgen Deprivation Therapy on Alzheimer's disease and Related Dementia Risk in the Million Veteran Program. Alzheimers Dement 2022. [DOI: 10.1002/alz.064965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | - Rishi Deka
- University of California San Diego La Jolla CA USA
| | - Tori Anglin
- VA Informatics and Computing Infrastructure (VINCI) Salt Lake City UT USA
| | - Mark W. Logue
- National Center for PTSD, VA Boston Healthcare System Boston MA USA
| | | | | | | | - Guneet Jasuja
- Center for Healthcare Organization and Implementation Research, VA Bedford Health Care System Bedford MA USA
| | - Kyung‐Min Lee
- VA Salt Lake City Healthcare System Salt Lake City UT USA
| | - Julie Lynch
- VA Informatics and Computing Infrastructure (VINCI) Salt Lake City UT USA
| | | | - Brenton Rose
- University of California San Diego La Jolla CA USA
| | | | - Craig Teerlink
- University of Utah School of Medicine Salt Lake City UT USA
| | - Xin M Tu
- University of California, San Diego La Jolla CA USA
| | - Richard L. Hauger
- Center for Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System San Diego CA USA
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19
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Quach NE, Yang K, Chen R, Tu J, Xu M, Tu XM, Zhang X. Post-hoc power analysis: a conceptually valid approach for power based on observed study data. Gen Psychiatr 2022; 35:e100764. [PMID: 36189182 PMCID: PMC9472103 DOI: 10.1136/gpsych-2022-100764] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
Power analysis is a key component of planning prospective studies such as clinical trials. However, some journals in biomedical and psychosocial sciences request power analysis for data already collected and analysed before accepting manuscripts for publication. Many have raised concerns about the conceptual basis for such post-hoc power analyses. More recently, Zhang et al showed by using simulation studies that such power analyses do not indicate true power for detecting statistical significance since post-hoc power estimates vary in the range of practical interests and can be very different from the true power. On the other hand, journals’ request for information about the reliability of statistical findings in a manuscript due to small sample sizes is justified since the sample size plays an important role in the reproducibility of statistical findings. The problem is the wording of the journals' request, as the current power analysis paradigm is not designed to address journals’ concerns about the reliability of the statistical findings. In this paper, we propose an alternate formulation of power analysis to provide a conceptually valid approach to the journals’ wrongly worded but practically significant concern.
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Affiliation(s)
- Natalie E Quach
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Kun Yang
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Ruohui Chen
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Justin Tu
- Department of Orthopedics, Emory Healthcare, Emory University, Atlanta, Georgia, USA
| | - Manfei Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Xinlian Zhang
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
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20
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Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations Between Depression and Cardiometabolic Health: A 27-Year Longitudinal Study - Corrigendum. Psychol Med 2022; 52:3018. [PMID: 36177891 DOI: 10.1017/s0033291722003105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Hillary L Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Mark W Logue
- Research Service, VA Boston Healthcare System, Boston, MA, USA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Ruth E McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Kristy N Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Graham M L Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - McKenna E Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Richard L Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Amy J Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice, Saint Louis, MO, USA
| | - William S Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
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21
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Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations between depression and cardiometabolic health: A 27-year longitudinal study. Psychol Med 2022; 52:3007-3017. [PMID: 33431106 PMCID: PMC8547283 DOI: 10.1017/s003329172000505x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems. METHODS The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse ('baseline') and the longitudinal Vietnam Era Twin Study of Aging ('follow-up'). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)]. RESULTS Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07-1.57), erectile dysfunction (OR 1.32, 95% CI 1.10-1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04-1.53), and sleep apnea (OR 1.40, 95% CI 1.13-1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09-1.60). CONCLUSIONS A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
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Affiliation(s)
- Hillary L. Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Mark W. Logue
- Research Service, VA Boston Healthcare System, Boston, MA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E. Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Kristy N. Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | | | - Graham M. L. Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Jeremy A. Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - McKenna E. Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Lisa T. Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Nathan A. Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Richard L. Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Amy J. Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael C. Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Xin M. Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice
| | - William S. Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
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22
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Elman JA, Vogel JW, Bocancea DI, Ossenkoppele R, van Loenhoud AC, Tu XM, Kremen WS. Issues and recommendations for the residual approach to quantifying cognitive resilience and reserve. Alzheimers Res Ther 2022; 14:102. [PMID: 35879736 PMCID: PMC9310423 DOI: 10.1186/s13195-022-01049-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 07/14/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Cognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances. METHODS AND RESULTS We describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against "pre-regression" strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience. CONCLUSIONS Caution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline.
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Affiliation(s)
- Jeremy A. Elman
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California San Diego, 9500 Gilman Dr. (MC0738), La Jolla, CA 92093 USA ,grid.266100.30000 0001 2107 4242Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA USA
| | - Jacob W. Vogel
- grid.25879.310000 0004 1936 8972Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Diana I. Bocancea
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Rik Ossenkoppele
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XVU University Medical Center, Amsterdam, the Netherlands ,grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Anna C. van Loenhoud
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XVU University Medical Center, Amsterdam, the Netherlands
| | - Xin M. Tu
- grid.266100.30000 0001 2107 4242Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - William S. Kremen
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California San Diego, 9500 Gilman Dr. (MC0738), La Jolla, CA 92093 USA ,grid.266100.30000 0001 2107 4242Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA USA
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23
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Lu Y, Zhao Q, Zou J, Yan S, Tamaresis JS, Nelson L, Tu XM, Chen J, Tian L. A Composite Endpoint for Treatment Benefit According to Patient Preference. Stat Biopharm Res 2022; 14:408-422. [PMID: 37981982 PMCID: PMC10655937 DOI: 10.1080/19466315.2022.2085783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/20/2022] [Accepted: 05/25/2022] [Indexed: 10/18/2022]
Abstract
Complex disorders usually affect multiple symptom domains measured by several outcomes. The importance of these outcomes is often different among patients. Current approaches integrate multiple outcomes without considering patient preferences at the individual level. In this paper, we propose a new composite Desirability of Outcome Ranking (DOOR) that integrates individual level ranking of outcome importance and define a winning probability measuring the overall treatment effect. Stratified randomization can be performed based on the participants' baseline outcome rankings. A Wilcoxon-Mann-Whitney U-statistic is used to average the pairwise DOOR between one treated and one control patient, considering the difference in these patients' ranking of outcome importance. We use both theoretical and empirical methods to examine the statistical properties of our method and to compare with conventional approaches. We conclude that the proposed composite DOOR properly reflects patient-level preferences and can be used in pivotal trials or comparative effectiveness trials for a patient-centered evaluation of overall treatment benefits.
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Affiliation(s)
- Ying Lu
- Department of Biomedical Data Science, Stanford University School of Medicine
- Department of Epidemiology and Population Health, Stanford University School of Medicine
| | - Qian Zhao
- Department of Biomedical Data Science, Stanford University School of Medicine
- Department of Biostatistics, Guangzhou Medical University
| | - Jiying Zou
- Department of Statistics, Stanford University
| | - Shiyan Yan
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences
| | - John S. Tamaresis
- Department of Biomedical Data Science, Stanford University School of Medicine
| | - Lorene Nelson
- Department of Epidemiology and Population Health, Stanford University School of Medicine
| | - Xin M. Tu
- Department of Family Medicine and Health Sciences, University of California, San Diego
| | | | - Lu Tian
- Department of Biomedical Data Science, Stanford University School of Medicine
- Department of Statistics, Stanford University
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24
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Abstract
OBJECTIVES Wisdom is a personality trait comprising seven components: self-reflection, pro-social behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality. Wisdom, a potentially modifiable trait, is strongly associated with well-being. We have published a validated 28-item San Diego Wisdom Scale, the SD-WISE-28. Brief scales are necessary for use in large population-based studies and in clinical practice. The present study aimed to create an abbreviated 7-item version of the SD-WISE. METHOD Participants included 2093 people, aged 20-82 years, recruited and surveyed through the online crowdsourcing platform Amazon Mechanical Turk. The participants' mean age was 46 years, with 55% women. Participants completed the SD-WISE-28 as well as validation scales for various positive and negative constructs. Psychometric analyses (factor analysis and item response theory) were used to select one item from each of the seven SD-WISE-28 subscales. RESULTS We selected a combination of items that produced acceptable unidimensional model fit and good reliability (ω = 0.74). Item statistics suggested that all seven items were strong indicators of wisdom, although the association was weakest for spirituality. Analyses indicated that the 28-item and 7-item SD-WISE are both very highly correlated (r = 0.92) and produce a nearly identical pattern of correlations with demographic and validity variables. CONCLUSION The SD-WISE-7, and its derived Jeste-Thomas Wisdom Index (JTWI) score, balances reliability and brevity for research applications.
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Affiliation(s)
- Michael L. Thomas
- Department of Psychology, Colorado State University, Fort Collins, Colorado, U.S.A
| | - Barton W. Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, U.S.A
- VA San Diego Healthcare System, San Diego, California, U.S.A
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
| | - Ellen E. Lee
- Department of Psychiatry, University of California San Diego, La Jolla, California, U.S.A
- VA San Diego Healthcare System, San Diego, California, U.S.A
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
| | - Jinyuan Liu
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
- Department of Mathematics, University of California San Diego, La Jolla, California, U.S.A
| | - Rebecca Daly
- Department of Psychiatry, University of California San Diego, La Jolla, California, U.S.A
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
| | - Xin M. Tu
- Department of Psychiatry, University of California San Diego, La Jolla, California, U.S.A
- VA San Diego Healthcare System, San Diego, California, U.S.A
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
| | - Dilip V. Jeste
- Department of Psychiatry, University of California San Diego, La Jolla, California, U.S.A
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, California, U.S.A
- Department of Neurosciences, University of California San Diego, La Jolla, California, U.S.A
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Davidson EJ, Taylor CT, Ayers CR, Quach NE, Tu XM, Lee EE. The Relationship Between Loneliness and Positive Affect in Older Adults. Am J Geriatr Psychiatry 2022; 30:678-685. [PMID: 34887211 PMCID: PMC9095765 DOI: 10.1016/j.jagp.2021.11.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/02/2021] [Accepted: 11/03/2021] [Indexed: 01/20/2023]
Abstract
OBJECTIVE To establish whether positive affect (PA) is uniquely associated with loneliness and other social functioning variables beyond negative affect (NA) among older adults. METHODS Four hundred and twenty-eight participants (aged 60+ years old, 82% White, and 48% female) were recruited using random digit-dialing and completed scales for loneliness (UCLA Loneliness Scale), companionship (PROMIS scale), satisfaction with discretionary social activities (PROMIS scale), PA (Center for Epidemiologic Studies [CES] Happiness Scale), and NA (CES-Depression scale and Brief Symptom Inventory-Anxiety Subscale). RESULTS Multiple linear regression models found PA to be a significant predictor of lower loneliness where the effect of PA on loneliness is dependent on the level of NA; a large effect size at the mean level of NA, which becomes attenuated when NA increases. Although the direction of effect of PA on loneliness will change for NA > 5.10, which is 5 standard deviations away from 0, based on the model estimates, the percent of subjects with this large NA levels is practically 0. Thus, higher PA is associated with lower loneliness, however this effect is attenuated for larger NA. Similarly, multiple linear regression models found that companionship was associated with PA and NA where the effect of PA is dependent on the level of NA; a medium effect size at the mean level of NA, which becomes attenuated when NA increases. As in the case of loneliness, the direction of effect of PA on companionship will change for NA > 3.52, which is 3.5 standard deviation away from 0, based on the model estimates, but the percent of subjects with this large NA levels is practically 0. Thus, higher PA is associated with increased companionship, aand this effect is attenuated with greater NA. Satisfaction with social activities was associated with PA only (medium effect size). CONCLUSION Results suggest PA appears to be uniquely associated with social functioning among older adults. These findings support the potential for treatments that target PA to decrease loneliness among older adults, or vice versa.
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Affiliation(s)
- Eliza J. Davidson
- Research Service, VA San Diego Healthcare System,San Diego State University/ University of California, San Diego Joint Doctoral Program in Clinical Psychology
| | - Charles T. Taylor
- San Diego State University/ University of California, San Diego Joint Doctoral Program in Clinical Psychology,Department of Psychiatry, University of California, San Diego School of Medicine
| | - Catherine R. Ayers
- Mental Healthcare Line, VA San Diego Healthcare System,Department of Psychiatry, University of California, San Diego School of Medicine
| | - Natalie E. Quach
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego
| | - Xin M. Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego
| | - Ellen E. Lee
- Mental Healthcare Line, VA San Diego Healthcare System,Department of Psychiatry, University of California, San Diego School of Medicine,Desert-Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, CA
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26
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Dave S, Yang K, Schnickel GT, Kono Y, Delebecque F, Arellano D, Liu A, Zhang X, Tu XM, Ajmera V. The Impact of Treatment of Hepatocellular Carcinoma With Immune Checkpoint Inhibitors on Pre- and Post-liver Transplant Outcomes. Transplantation 2022; 106:e308-e309. [PMID: 35616911 PMCID: PMC9937048 DOI: 10.1097/tp.0000000000004108] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Shravan Dave
- Division of Gastroenterology & Hepatology, Department of Medicine, University of California, San Diego, CA
| | - Kun Yang
- School of Public Health, University of California, San Diego, CA
| | - Gabriel T. Schnickel
- Division of Transplant and Hepatobiliary Surgery, Department of Surgery, University of California, San Diego, CA
| | - Yuko Kono
- Division of Gastroenterology & Hepatology, Department of Medicine, University of California, San Diego, CA
| | - Fanny Delebecque
- Altman Clinical and Translational Research Institute (ACTRI), University of California, San Diego, CA
| | - Deyna Arellano
- Altman Clinical and Translational Research Institute (ACTRI), University of California, San Diego, CA
| | - Amy Liu
- University of California, San Diego School of Medicine, San Diego, CA
| | - Xinlian Zhang
- School of Public Health, University of California, San Diego, CA
| | - Xin M. Tu
- School of Public Health, University of California, San Diego, CA
| | - Veeral Ajmera
- Division of Gastroenterology & Hepatology, Department of Medicine, University of California, San Diego, CA
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Abstract
Suppose we have a sample of subjects in two treatment groups. To study the difference of the treatment effects, we can analyse the data using all subjects (overall analysis). We may also divide the subjects into several subgroups based on some covariates of interest (eg, gender), and study the treatment effects within each subgroup. The results of these two analyses may be different or even in opposite directions. In this paper, we give a general sufficient condition of consistency between the overall and subgroup analyses.
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Affiliation(s)
- Hongyue Wang
- Departments of Biostatistics & Computational Biology, University of Rochester, Rochester, New York, USA
| | - Bokai Wang
- Departments of Biostatistics & Computational Biology, University of Rochester, Rochester, New York, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Changyong Feng
- Departments of Biostatistics & Computational Biology, University of Rochester, Rochester, New York, USA
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28
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Sanderson-Cimino M, Elman JA, Tu XM, Gross AL, Panizzon MS, Gustavson DE, Bondi MW, Edmonds EC, Eppig JS, Franz CE, Jak AJ, Lyons MJ, Thomas KR, Williams ME, Kremen WS. Practice Effects in Mild Cognitive Impairment Increase Reversion Rates and Delay Detection of New Impairments. Front Aging Neurosci 2022; 14:847315. [PMID: 35547623 PMCID: PMC9083463 DOI: 10.3389/fnagi.2022.847315] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/21/2022] [Indexed: 01/27/2023] Open
Abstract
Objective Cognitive practice effects (PEs) can delay detection of progression from cognitively unimpaired to mild cognitive impairment (MCI). They also reduce diagnostic accuracy as suggested by biomarker positivity data. Even among those who decline, PEs can mask steeper declines by inflating cognitive scores. Within MCI samples, PEs may increase reversion rates and thus impede detection of further impairment. Within an MCI sample at baseline, we evaluated how PEs impact prevalence, reversion rates, and dementia progression after 1 year. Methods We examined 329 baseline Alzheimer's Disease Neuroimaging Initiative MCI participants (mean age = 73.1; SD = 7.4). We identified test-naïve participants who were demographically matched to returnees at their 1-year follow-up. Since the only major difference between groups was that one completed testing once and the other twice, comparison of scores in each group yielded PEs. PEs were subtracted from each test to yield PE-adjusted scores. Biomarkers included cerebrospinal fluid phosphorylated tau and amyloid beta. Cox proportional models predicted time until first dementia diagnosis using PE-unadjusted and PE-adjusted diagnoses. Results Accounting for PEs increased MCI prevalence at follow-up by 9.2% (272 vs. 249 MCI), and reduced reversion to normal by 28.8% (57 vs. 80 reverters). PEs also increased stability of single-domain MCI by 12.0% (164 vs. 147). Compared to PE-unadjusted diagnoses, use of PE-adjusted follow-up diagnoses led to a twofold increase in hazard ratios for incident dementia. We classified individuals as false reverters if they reverted to cognitively unimpaired status based on PE-unadjusted scores, but remained classified as MCI cases after accounting for PEs. When amyloid and tau positivity were examined together, 72.2% of these false reverters were positive for at least one biomarker. Interpretation Even when PEs are small, they can meaningfully change whether some individuals with MCI retain the diagnosis at a 1-year follow-up. Accounting for PEs resulted in increased MCI prevalence and altered stability/reversion rates. This improved diagnostic accuracy also increased the dementia-predicting ability of MCI diagnoses.
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Affiliation(s)
- Mark Sanderson-Cimino
- University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,*Correspondence: Mark Sanderson-Cimino,
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Xin M. Tu
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA, United States,Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, San Diego, CA, United States
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MA, United States
| | - Matthew S. Panizzon
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Daniel E. Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mark W. Bondi
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Psychology Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Emily C. Edmonds
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Research Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Joel S. Eppig
- Rehabilitation Institute of Washington, Seattle, WA, United States
| | - Carol E. Franz
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Amy J. Jak
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
| | - Kelsey R. Thomas
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Research Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - McKenna E. Williams
- University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
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Gillespie NA, Hatton SN, Hagler DJ, Dale AM, Elman JA, McEvoy LK, Eyler LT, Fennema-Notestine C, Logue MW, McKenzie RE, Puckett OK, Tu XM, Whitsel N, Xian H, Reynolds CA, Panizzon MS, Lyons MJ, Neale MC, Kremen WS, Franz C. The Impact of Genes and Environment on Brain Ageing in Males Aged 51 to 72 Years. Front Aging Neurosci 2022; 14:831002. [PMID: 35493948 PMCID: PMC9051484 DOI: 10.3389/fnagi.2022.831002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/15/2022] [Indexed: 01/27/2023] Open
Abstract
Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimer's Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 51-72 years. Biometrical genetic analyses "twin models" revealed significant and highly correlated estimates of additive genetic heritability ranging from 59 to 75%. Multivariate longitudinal modeling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States,QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,*Correspondence: Nathan A. Gillespie,
| | - Sean N. Hatton
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Donald J. Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Anders M. Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States,Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, United States
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Linda K. McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Lisa T. Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, United States
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Mark W. Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States,Department of Psychiatry and Biomedical Genetics Section, Boston University School of Medicine, Boston, MA, United States,Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ruth E. McKenzie
- Department of Psychology, Boston University, Boston, MA, United States,School of Education and Social Policy, Merrimack College, North Andover, MA, United States
| | - Olivia K. Puckett
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Xin M. Tu
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Nathan Whitsel
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Hong Xian
- Department of Epidemiology and Biostatistics, Saint. Louis University, St. Louis, MO, United States,Research Service, VA St. Louis Healthcare System, St. Louis, MO, United States
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, United States
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States,Department of Biological Psychology, Free University of Amsterdam, Amsterdam, Netherlands
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA, United States,William S. Kremen,
| | - Carol Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Carol Franz,
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30
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Whitsel N, Reynolds CA, Buchholz EJ, Pahlen S, Pearce RC, Hatton SN, Elman JA, Gillespie NA, Gustavson DE, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McEvoy LK, McKenzie R, Neale MC, Panizzon MS, Sanderson-Cimino M, Toomey R, Tu XM, Williams MKE, Bell T, Xian H, Lyons MJ, Kremen WS, Franz CE. Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life. Addiction 2022; 117:1049-1059. [PMID: 34605095 PMCID: PMC8904283 DOI: 10.1111/add.15710] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 09/03/2021] [Accepted: 09/15/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND AIMS Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later. DESIGN Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated. SETTING Population-based United States sample. PARTICIPANTS/CASES Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves. MEASUREMENTS Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19). FINDINGS In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD. CONCLUSIONS Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.
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Affiliation(s)
- Nathan Whitsel
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Erik J Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Sean N Hatton
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Anders M Dale
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Donald J Hagler
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Linda K McEvoy
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Mc Kenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Tyler Bell
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St Louis University, St Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
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Sanderson‐Cimino M, Elman JA, Tu XM, Gross AL, Panizzon MS, Gustavson DE, Bondi MW, Edmonds EC, Eglit GM, Eppig JS, Franz CE, Jak AJ, Lyons MJ, Thomas KR, Williams ME, Kremen WS. Cognitive practice effects delay diagnosis of MCI: Implications for clinical trials. Alzheimers Dement (N Y) 2022; 8:e12228. [PMID: 35128027 PMCID: PMC8804942 DOI: 10.1002/trc2.12228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 07/12/2021] [Accepted: 11/15/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Practice effects (PEs) on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). Importantly, PEs may be present even when there are performance declines, if scores would have been even lower without prior test exposure. We assessed how accounting for PEs using a replacement-participants method impacts incident MCI diagnosis. METHODS Of 889 baseline cognitively normal (CN) Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 722 returned 1 year later (mean age = 74.9 ± 6.8 at baseline). The scores of test-naïve demographically matched "replacement" participants who took tests for the first time were compared to returnee scores at follow-up. PEs-calculated as the difference between returnee follow-up scores and replacement participants scores-were subtracted from follow-up scores of returnees. PE-adjusted cognitive scores were then used to determine if individuals were below the impairment threshold for MCI. Cerebrospinal fluid amyloid beta, phosphorylated tau, and total tau were used for criterion validation. In addition, based on screening and recruitment numbers from a clinical trial of amyloid-positive individuals, we estimated the effect of earlier detection of MCI by accounting for cognitive PEs on a hypothetical clinical trial in which the key outcome was progression to MCI. RESULTS In the ADNI sample, PE-adjusted scores increased MCI incidence by 19% (P < .001), increased proportion of amyloid-positive MCI cases (+12%), and reduced proportion of amyloid-positive CNs (-5%; P's < .04). Additional calculations showed that the earlier detection and increased MCI incidence would also substantially reduce necessary sample size and study duration for a clinical trial of progression to MCI. Cost savings were estimated at ≈$5.41 million. DISCUSSION Detecting MCI as early as possible is of obvious importance. Accounting for cognitive PEs with the replacement-participants method leads to earlier detection of MCI, improved diagnostic accuracy, and can lead to multi-million-dollar cost reductions for clinical trials.
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Affiliation(s)
- Mark Sanderson‐Cimino
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical PsychologySan DiegoCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Jeremy A. Elman
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Xin M. Tu
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Family Medicine and Public HealthUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Alden L. Gross
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Matthew S. Panizzon
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Daniel E. Gustavson
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Mark W. Bondi
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Psychology ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Emily C. Edmonds
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Research ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Graham M.L. Eglit
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | | | - Carol E. Franz
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Amy J. Jak
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Center of Excellence for Stress and Mental HealthVeterans Affairs San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Michael J. Lyons
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
| | - Kelsey R. Thomas
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Research ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - McKenna E. Williams
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical PsychologySan DiegoCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - William S. Kremen
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
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Aslam S, Liu J, Sigler R, Syed RR, Tu XM, Little SJ, De Gruttola V. COVID-19 vaccination is protective of clinical disease in solid organ transplant recipients. Transpl Infect Dis 2022; 24:e13788. [PMID: 34989104 DOI: 10.1111/tid.13788] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 12/15/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Clinical effectiveness of coronavirus disease 2019 (COVID-19) vaccination in solid organ transplant recipients (SOTR) is not well documented despite multiple studies demonstrating sub-optimal immunogenicity. METHODS We reviewed medical records of eligible SOTRs at a single center to assess vaccination status and identify cases of symptomatic COVID-19 from 1/1/2021-8/12/2021. We developed a Cox proportional hazards model using date of vaccination and time since transplantation as a time varying covariate with age and gender as potential time-invariant confounders. Survival curves were created using the parameters estimated from the Cox model. RESULTS Among 1904 SOTRs, 1362 were fully vaccinated (96% received mRNA vaccines) and 542 were either unvaccinated (n = 470) or partially vaccinated (n = 72). There were 115 cases of COVID-19, of which 12 occurred in fully vaccinated individuals. Cox regression with date of vaccination and time since transplantation as the time-varying co-variates showed that after baseline adjustment for age and sex, being fully vaccinated had a significantly lower hazard for COVID-19, hazard ratio = 0.29, 95% confidence interval (0.09, 0.91). CONCLUSION We found that 2-dose mRNA COVID-19 vaccination was protective of symptomatic COVID-19 in vaccinated vs. unvaccinated SOTRs. TWEET COVID-19 vaccination was associated with significantly lower hazard for symptomatic COVID-19 (HR 0.29, 95% CI 0.09, 0.91) among 1904 SOT recipients at a single center from 1/1/2021-8/12/2021. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Saima Aslam
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Jinyuan Liu
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Rachel Sigler
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Rehan R Syed
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Xin M Tu
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Susan J Little
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA
| | - Victor De Gruttola
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA
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Liu C, Zhang X, Nguyen TT, Liu J, Wu T, Lee E, Tu XM. Partial least squares regression and principal component analysis: similarity and differences between two popular variable reduction approaches. Gen Psychiatr 2022; 35:e100662. [PMID: 35146334 PMCID: PMC8796256 DOI: 10.1136/gpsych-2021-100662] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 12/29/2021] [Indexed: 01/08/2023] Open
Abstract
In many statistical applications, composite variables are constructed to reduce the number of variables and improve the performances of statistical analyses of these variables, especially when some of the variables are highly correlated. Principal component analysis (PCA) and factor analysis (FA) are generally used for such purposes. If the variables are used as explanatory or independent variables in linear regression analysis, partial least squares (PLS) regression is a better alternative. Unlike PCA and FA, PLS creates composite variables by also taking into account the response, or dependent variable, so that they have higher correlations with the response than composites from their PCA and FA counterparts. In this report, we provide an introduction to this useful approach and illustrate it with data from a real study.
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Affiliation(s)
- Chenyu Liu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Xinlian Zhang
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Tanya T Nguyen
- Department of Psychiatry, Stein Institute for Research on Aging, UC San Diego, La Jolla, California, USA
| | - Jinyuan Liu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Tsungchin Wu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
| | - Ellen Lee
- Department of Psychiatry, Stein Institute for Research on Aging, UC San Diego, La Jolla, California, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, California, USA
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Eglit GML, Elman JA, Panizzon MS, Sanderson-Cimino M, Williams ME, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Gustavson DE, Hatton SN, Hagler DJ, Hauger RL, Jak AJ, Logue MW, McEvoy LK, McKenzie RE, Neale MC, Puckett O, Reynolds CA, Toomey R, Tu XM, Whitsel N, Xian H, Lyons MJ, Franz CE, Kremen WS. Paradoxical cognitive trajectories in men from earlier to later adulthood. Neurobiol Aging 2022; 109:229-238. [PMID: 34785406 PMCID: PMC8715388 DOI: 10.1016/j.neurobiolaging.2021.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 10/07/2021] [Accepted: 10/07/2021] [Indexed: 01/03/2023]
Abstract
Because longitudinal studies of aging typically lack cognitive data from earlier ages, it is unclear how general cognitive ability (GCA) changes throughout the life course. In 1173 Vietnam Era Twin Study of Aging (VETSA) participants, we assessed young adult GCA at average age 20 and current GCA at 3 VETSA assessments beginning at average age 56. The same GCA index was used throughout. Higher young adult GCA and better GCA maintenance were associated with stronger specific cognitive abilities from age 51 to 73. Given equivalent GCA at age 56, individuals who had higher age 20 GCA outperformed those whose GCA remained stable in terms of memory, executive function, and working memory abilities from age 51 to 73. Thus, paradoxically, despite poorer maintenance of GCA, high young adult GCA still conferred benefits. Advanced predicted brain age and the combination of elevated vascular burden and APOE-ε4 status were associated with poorer maintenance of GCA. These findings highlight the importance of distinguishing between peak and current GCA for greater understanding of cognitive aging.
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Affiliation(s)
- Graham M L Eglit
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA.
| | - Jeremy A Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mathew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; San Diego State University/University of California, San Diego Joint Doctoral Program, San Diego, CA, USA
| | - McKenna E Williams
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; San Diego State University/University of California, San Diego Joint Doctoral Program, San Diego, CA, USA
| | - Anders M Dale
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel E Gustavson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Sean N Hatton
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Richard L Hauger
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Amy J Jak
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Mark W Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA; Psychiatry and Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Ruth E McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA; School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Olivia Puckett
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Nathan Whitsel
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Michael J Lyons
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
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35
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Zhang S, Tu XM. Tests for comparing time‐invariant and time‐varying spectra based on the Anderson–Darling statistic. STAT NEERL 2021. [DOI: 10.1111/stan.12259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Shibin Zhang
- Department of Mathematics Shanghai Normal University Shanghai China
| | - Xin M. Tu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health UC San Diego La Jolla California USA
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Franz CE, Whitsell N, Qin YA, Tu XM, Kremen WS. Associations of smoking and biohazard exposure with Alzheimer’s disease brain and plasma biomarkers in early old age. Alzheimers Dement 2021. [DOI: 10.1002/alz.056627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
| | | | | | - Xin M Tu
- University of California, San Diego La Jolla CA USA
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Sanderson‐Cimino ME, Elman JA, Tu XM, Panizzon MS, Jak AJ, Franz CE, Kremen WS. Accounting for practice effects improves stability of MCI diagnosis and uncovers new impairments. Alzheimers Dement 2021. [DOI: 10.1002/alz.056630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | | | - Xin M Tu
- University of California, San Diego La Jolla CA USA
| | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
| | - Carol E. Franz
- University of California, San Diego La Jolla CA USA
- Vietnam Era Twin Study of Aging La Jolla CA USA
| | - William S. Kremen
- University of California, San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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Franz CE, Hatton SN, Elman JA, Warren T, Gillespie NA, Whitsel NA, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McKenzie R, Neale MC, Panizzon MS, Pearce RC, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Williams M, Xian H, Lyons MJ, Kremen WS. Lifestyle and the aging brain: interactive effects of modifiable lifestyle behaviors and cognitive ability in men from midlife to old age. Neurobiol Aging 2021; 108:80-89. [PMID: 34547718 PMCID: PMC8862767 DOI: 10.1016/j.neurobiolaging.2021.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 07/23/2021] [Accepted: 08/12/2021] [Indexed: 01/18/2023]
Abstract
We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals.
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Affiliation(s)
- Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA.
| | - Sean N Hatton
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Teresa Warren
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Nathan A Whitsel
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine, University of California San Diego, San Diego, CA, USA
| | - McKenna Williams
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
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Dickson SD, Thomas IC, Bhatia HS, Nishimura M, Mahmud E, Tu XM, Lin T, Adler E, Greenberg B, Alshawabkeh L. Methamphetamine-Associated Heart Failure Hospitalizations Across the United States: Geographic and Social Disparities. J Am Heart Assoc 2021; 10:e018370. [PMID: 34365802 PMCID: PMC8475042 DOI: 10.1161/jaha.120.018370] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Although methamphetamine abuse is associated with the development of heart failure (HF), nationwide data on methamphetamine-associated HF (MethHF) hospitalizations are limited. This study evaluates nationwide HF hospitalizations associated with substance abuse to better understand MethHF prevalence trends and the clinical characteristics of those patients. Methods and Results This cross-sectional period-prevalence study used hospital discharge data from the National Inpatient Sample to identify adult primary HF hospitalizations with a secondary diagnosis of abuse of methamphetamines, cocaine, or alcohol in the United States from 2002 to 2014. All 2014 MethHF admissions were separated by regional census division to evaluate geographical distribution. Demographics, payer information, and clinical characteristics of MethHF hospitalizations were compared with all other HF hospitalizations. Total nationwide MethHF hospitalizations increased from 547 in 2002 to 6625 in 2014 with a predominance on the West Coast. Methamphetamine abuse was slightly more common among primary HF hospitalizations compared with all-cause hospitalizations (7.4 versus 6.4 per 1000; Cohen h=0.012; P<0.001). Among HF hospitalizations, patients with MethHF were younger (mean age, 48.9 versus 72.4 years; Cohen d=1.93; P<0.001), more likely to be on Medicaid (59.4% versus 8.8%; Cohen h=1.16; P<0.001) or uninsured (12.0% versus 2.6%; Cohen h=0.36; P<0.001), and more likely to present to urban hospitals (43.8% versus 28.3%; Cohen h=0.32; P<0.001) than patients with non-methamphetamine associated HF. Patients with MethHF had higher rates of psychiatric comorbidities and were more likely to leave the hospital against medical advice. Conclusions MethHF hospitalizations have significantly increased in the United States, particularly on the West Coast. Coordinated public health policies and systems of care are needed to address this rising epidemic.
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Affiliation(s)
- Stephen D Dickson
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Isac C Thomas
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Harpreet S Bhatia
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Marin Nishimura
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Ehtisham Mahmud
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Xin M Tu
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Tuo Lin
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Eric Adler
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Barry Greenberg
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
| | - Laith Alshawabkeh
- Division of Cardiovascular Medicine Department of Medicine University of California San Diego La Jolla CA
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Williams ME, Elman JA, McEvoy LK, Andreassen OA, Dale AM, Eglit GML, Eyler LT, Fennema-Notestine C, Franz CE, Gillespie NA, Hagler DJ, Hatton SN, Hauger RL, Jak AJ, Logue MW, Lyons MJ, McKenzie RE, Neale MC, Panizzon MS, Puckett OK, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Whitsel N, Xian H, Kremen WS. 12-year prediction of mild cognitive impairment aided by Alzheimer's brain signatures at mean age 56. Brain Commun 2021; 3:fcab167. [PMID: 34396116 PMCID: PMC8361427 DOI: 10.1093/braincomms/fcab167] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 04/26/2021] [Accepted: 05/10/2021] [Indexed: 01/22/2023] Open
Abstract
Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer's disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Towards that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: (i) a validated MRI-derived Alzheimer's disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and (ii) a novel grey matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246-367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51-60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer's disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61-71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply ageing-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P = 0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step towards improving very early identification of Alzheimer's disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo 0316, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0372, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Graham M L Eglit
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA 92093, USA
| | - Amy J Jak
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- VA San Diego Healthcare System, San Diego, CA 92093, USA
| | - Mark W Logue
- National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Psychiatry and the Biomedical Genetics Section, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212, USA
| | - Ruth E McKenzie
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- School of Education and Social Policy, Merrimack College, North Andover, MA 01845, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Olivia K Puckett
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA 92521, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212, USA
| | - Xin M Tu
- Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
| | - Nathan Whitsel
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Hong Xian
- Department of Biostatistics, St. Louis University, St. Louis, MO 63103, USA
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA 92093, USA
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Block RC, Shearer GC, Holub A, Tu XM, Mousa S, Brenna JT, Harris WS, Tintle N. Aspirin and omega-3 fatty acid status interact in the prevention of cardiovascular diseases in Framingham Heart Study. Prostaglandins Leukot Essent Fatty Acids 2021; 169:102283. [PMID: 33964664 PMCID: PMC8159885 DOI: 10.1016/j.plefa.2021.102283] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 03/18/2021] [Accepted: 04/12/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND The roles of omega-3 (n3) fatty acids [eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)] and low-dose aspirin in the primary prevention of ischemic cardiovascular disease (CVD) are controversial. Since omega-3 (n3) fatty acids and aspirin affect cyclooxygenase activity in platelets, there could be a clinically-relevant effect of aspirin combined with a particular n3 fatty acid level present in each individual. METHODS RBC EPA+DHA, arachidonic acid (AA) and docosapentaenoic acid (DPA) were measured in 2500 participants without known CVD in the Framingham Heart Study. We then tested for interactions with reported aspirin use (1004 reported use and 1494 did not) on CVD outcomes. The median follow-up was 7.2 years. RESULTS Having RBC EPA+DHA in the second quintile (4.2-4.9% of total fatty acids) was associated with significantly reduced risk for future CVD events (relative to the first quintile, <4.2%) in those who did not take aspirin (HR 0.54 (0.30, 0.98)), but in those reporting aspirin use, risk was significantly increased (HR 2.16 (1.19, 3.92)) in this quintile. This interaction remained significant when adjusting for confounders. Significant interactions were also present for coronary heart disease and stroke outcomes using the same quintiles. Similar findings were present for EPA and DHA alone but not for DPA and AA. CONCLUSIONS There is a complex interaction between aspirin use and RBC EPA+DHA levels on CVD outcomes. This suggests that aspirin use may be beneficial in one omega-3 environment but harmful in another, implying that a personalized approach to both aspirin use and omega-3 supplementation may be needed.
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Affiliation(s)
- Robert C Block
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States; Cardiology Division, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States.
| | - Gregory C Shearer
- Department of Nutritional Sciences, Pennsylvania State University, University Park, Pennsylvania, United States
| | - Ashley Holub
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California, San Diego, United States
| | - Shaker Mousa
- The Pharmaceutical Research Institute, Albany College of Pharmacy and Health Sciences, Rensselaer, NY, United States
| | - J Thomas Brenna
- Departments of Pediatrics, Human Nutrition, and Chemistry, Dell Pediatric Research Institute, University of Texas at Austin, United States
| | - William S Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota; and OmegaQuant Analytics, LLC, Sioux Falls, SD, United States
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt University, Sioux Center, Iowa, United States
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LeardMann CA, McMaster HS, Warner S, Esquivel AP, Porter B, Powell TM, Tu XM, Lee WW, Rull RP, Hoge CW. Comparison of Posttraumatic Stress Disorder Checklist Instruments From Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition vs Fifth Edition in a Large Cohort of US Military Service Members and Veterans. JAMA Netw Open 2021; 4:e218072. [PMID: 33904913 PMCID: PMC8080232 DOI: 10.1001/jamanetworkopen.2021.8072] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
IMPORTANCE The definition of posttraumatic stress disorder (PTSD) changed markedly between the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) and DSM-5, creating challenges for studies and in medical settings spanning this transition. OBJECTIVE To evaluate the ability to compare and assess PTSD, based on DSM-IV and DSM-5 criteria, using PTSD Checklists (PCLs). DESIGN, SETTING, AND PARTICIPANTS This diagnostic study was conducted with survey data collected in October 2019, from the Millennium Cohort Study, a population-based US military cohort study. The population for the present study was restricted to a subset of initial web responders of the 2019 survey cycle, randomly assigned to 1 of 4 survey groups. EXPOSURES Each group received the DSM-IV and DSM-5 PCL (PCL-Civilian [PCL-C] version and PCL for DSM-5 [PCL-5]). PCL instruments were counterbalanced to control for order effects. MAIN OUTCOMES AND MEASURES Survey data were used to assess PTSD (using the PCL-C and PCL-5), major depressive disorder (using the Patient Health Questionnaire), generalized anxiety (using the Generalized Anxiety Disorder scale), and problem drinking (using the Patient Health Questionnaire). Demographic and military characteristics included age, sex, race/ethnicity, marital status, education, service branch, pay grade, enrollment panel, and military service status. RESULTS Among the 1921 participants (mean [SD] age, 50.1 [12.5] years), 1358 (70.7%) were men, 1638 (85.3%) were non-Hispanic White individuals, 1440 (75.0%) were married, and 1190 (61.9%) had at least a bachelor's degree; 295 (15.4%) had probable PTSD according to DSM-IV criteria with PCL-C compared with 286 (14.9%) using DSM-5 criteria with PCL-5 (κ = 0.77). There was substantial agreement between PCLs for probable PTSD based on DSM-IV criteria (295 [15.4%] with PCL-C; 316 [16.4%] with PCL-5; κ = 0.80) and DSM-5 criteria (286 [14.9%] with PCL-5; 258 [13.4%] with PCL-C; κ = 0.77). Estimated PTSD sum scores showed excellent agreement with observed scores. Using an established crosswalk, PCL-5 sum scores estimated with the PCL-C were similar to observed PCL-5 scores. Of the 17 corresponding items between the 2 instruments, 16 had substantial agreement. Appending 2 additional PCL-C items to the PCL-5 did not significantly alter estimates. The PCL-C and PCL-5 had nearly identical associations with comorbid conditions. CONCLUSIONS AND RELEVANCE The findings of this diagnostic study suggest that PTSD can be successfully assessed and compared over time with either PCL instrument in veteran and military populations.
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Affiliation(s)
- Cynthia A. LeardMann
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Hope Seib McMaster
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Steven Warner
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Alejandro P. Esquivel
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Ben Porter
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
- Social Science Research Center, Mississippi State University, Starkville
| | - Teresa M. Powell
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Xin M. Tu
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla
| | - William W. Lee
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
- Leidos, San Diego, California
| | - Rudolph P. Rull
- Deployment Health Research Department, Naval Health Research Center, San Diego, California
| | - Charles W. Hoge
- Center for Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, Maryland
- Office of the Army Surgeon General, Falls Church, Virginia
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Nguyen TT, Zhang X, Wu TC, Liu J, Le C, Tu XM, Knight R, Jeste DV. Association of Loneliness and Wisdom With Gut Microbial Diversity and Composition: An Exploratory Study. Front Psychiatry 2021; 12:648475. [PMID: 33841213 PMCID: PMC8029068 DOI: 10.3389/fpsyt.2021.648475] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 03/08/2021] [Indexed: 12/17/2022] Open
Abstract
Loneliness and wisdom have opposite effects on health and well-being. Loneliness is a serious public health problem associated with increased morbidity and mortality. Wisdom is associated with better health and well-being. We have consistently found a strong negative correlation between loneliness and wisdom. The present study aimed to investigate the association of loneliness and wisdom with the gut microbiome. One hundred eighty-four community-dwelling adults (28-97 years) completed validated self-report-based measures of loneliness, wisdom, compassion, social support, and social engagement. Fecal samples were collected and profiled using 16S rRNA sequencing. Linear regression analyses, controlling for age and body mass index, revealed that lower levels of loneliness and higher levels of wisdom, compassion, social support, and social engagement were associated with greater phylogenetic richness and diversity of the gut microbiome. Partial least squares (PLS) analysis to investigate multivariate relationships extracted two composite variables. Linear regression model predicting alpha-diversity with PLS components revealed that a linear combination of all psychosocial predictors (with negative loading for loneliness and positive loadings for all others, including wisdom, compassion, social support, and social engagement) was significantly associated with alpha-diversity. For beta-diversity, compassion and wisdom accounted for a significant proportion of variance in overall microbial community composition. Findings may have implications for interventions to reduce loneliness and possibly its health-related adverse consequences. Future research should explore whether increasing compassion and wisdom may improve loneliness and overall well-being as well as microbial diversity.
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Affiliation(s)
- Tanya T. Nguyen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Veterans Affairs San Diego Healthcare System, La Jolla, CA, United States
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
| | - Xinlian Zhang
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States
| | - Tsung-Chin Wu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States
| | - Jinyuan Liu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States
| | - Collin Le
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
| | - Xin M. Tu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States
| | - Rob Knight
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, United States
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, United States
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
| | - Dilip V. Jeste
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
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Elman JA, Puckett OK, Beck A, Fennema-Notestine C, Cross LK, Dale AM, Eglit GML, Eyler LT, Gillespie NA, Granholm EL, Gustavson DE, Hagler DJ, Hatton SN, Hauger R, Jak AJ, Logue MW, McEvoy LK, McKenzie RE, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Whitsel N, Williams ME, Xian H, Lyons MJ, Franz CE, Kremen WS. MRI-assessed locus coeruleus integrity is heritable and associated with multiple cognitive domains, mild cognitive impairment, and daytime dysfunction. Alzheimers Dement 2021; 17:1017-1025. [PMID: 33580733 PMCID: PMC8248066 DOI: 10.1002/alz.12261] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 10/12/2020] [Accepted: 11/10/2020] [Indexed: 12/22/2022]
Abstract
Introduction The locus coeruleus (LC) undergoes extensive neurodegeneration in early Alzheimer's disease (AD). The LC is implicated in regulating the sleep–wake cycle, modulating cognitive function, and AD progression. Methods Participants were 481 men (ages 62 to 71.7) from the Vietnam Era Twin Study of Aging. LC structural integrity was indexed by neuromelanin‐sensitive magnetic resonance imaging (MRI) contrast‐to‐noise ratio (LCCNR). We examined LCCNR, cognition, amnestic mild cognitive impairment (aMCI), and daytime dysfunction. Results Heritability of LCCNR was .48. Participants with aMCI showed greater daytime dysfunction. Lower LCCNR was associated with poorer episodic memory, general verbal fluency, semantic fluency, and processing speed, as well as increased odds of aMCI and greater daytime dysfunction. Discussion Reduced LC integrity is associated with widespread differences across cognitive domains, daytime sleep‐related dysfunction, and risk for aMCI. These findings in late‐middle‐aged adults highlight the potential of MRI‐based measures of LC integrity in early identification of AD risk.
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Affiliation(s)
- Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Latonya K Cross
- Department of Psychology, University of Hawaii Hilo, Hilo, Hawaii, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA.,Department of Neuroscience, University of California San Diego, La Jolla, California, USA
| | - Graham M L Eglit
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Eric L Granholm
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Department of Neuroscience, University of California San Diego, La Jolla, California, USA
| | - Richard Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Amy J Jak
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Mark W Logue
- National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Psychiatry and the Biomedical Genetics Section, Boston University School of Medicine, Boston, Massachusetts, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Ruth E McKenzie
- School of Education and Public Policy, Merrimack College, Andover, Massachusetts, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State/University of California, San Diego, California, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Xin M Tu
- Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA
| | - Nathan Whitsel
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State/University of California, San Diego, California, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, Missouri, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
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Lin T, Chen T, Liu J, Tu XM. Extending the Mann-Whitney-Wilcoxon rank sum test to survey data for comparing mean ranks. Stat Med 2021; 40:1705-1717. [PMID: 33398899 DOI: 10.1002/sim.8865] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 10/10/2020] [Accepted: 12/14/2020] [Indexed: 11/10/2022]
Abstract
Statistical methods for analysis of survey data have been developed to facilitate research. More recently, Lumley and Scott (2013) developed an approach to extend the Mann-Whitney-Wilcoxon (MWW) rank sum test to survey data. Their approach focuses on the null of equal distribution. In many studies, the MWW test is called for when two-sample t-tests (with or without equal variance assumed) fail to provide meaningful results, as they are highly sensitive to outliers. In such situations, the null of equal distribution is too restrictive, as interest lies in comparing centers of groups. In this article, we develop an approach to extend the MWW test to survey data to test the null of equal mean rank. Although not as popular as the mean and median, the mean rank is also a meaningful measure of the center of a distribution and is the same as the median for a symmetric distribution. We illustrate the proposed approach and show major differences with Lumley and Scott's alternative using both real and simulated data.
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Affiliation(s)
- Tuo Lin
- Department of Family Medicine and Public Health, UC San Diego, San Diego, California, USA
| | - Tian Chen
- Department of Mathematics, University of Toledo, Toledo, Ohio, USA
| | - Jinyuan Liu
- Department of Family Medicine and Public Health, UC San Diego, San Diego, California, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, UC San Diego, San Diego, California, USA
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46
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Treichler EBH, Palmer BW, Wu TC, Thomas ML, Tu XM, Daly R, Lee EE, Jeste DV. Women and Men Differ in Relative Strengths in Wisdom Profiles: A Study of 659 Adults Across the Lifespan. Front Psychol 2021; 12:769294. [PMID: 35185678 PMCID: PMC8850272 DOI: 10.3389/fpsyg.2021.769294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/16/2021] [Indexed: 01/14/2023] Open
Abstract
Wisdom is a multi-component trait that is important for mental health and well-being. In this study, we sought to understand gender differences in relative strengths in wisdom. A total of 659 individuals aged 27-103 years completed surveys including the 3-Dimensional Wisdom Scale (3D-WS) and the San Diego Wisdom Scale (SD-WISE). Analyses assessed gender differences in wisdom and gender's moderating effect on the relationship between wisdom and associated constructs including depression, loneliness, well-being, optimism, and resilience. Women scored higher on average on the 3D-WS but not on the SD-WISE. Women scored higher on compassion-related domains and on SD-WISE Self-Reflection. Men scored higher on cognitive-related domains and on SD-WISE Emotion Regulation. There was no impact of gender on the relationships between wisdom and associated constructs. Women and men have different relative strengths in wisdom, likely driven by sociocultural and biological factors. Tailoring wisdom interventions to individuals based on their profiles is an important next step.
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Affiliation(s)
- Emily B H Treichler
- VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States.,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States.,Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, San Diego, CA, United States
| | - Barton W Palmer
- VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States.,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States.,VA San Diego Healthcare System, San Diego, CA, United States
| | - Tsung-Chin Wu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, San Diego, CA, United States.,Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA, United States
| | - Michael L Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Xin M Tu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, San Diego, CA, United States.,Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA, United States
| | - Rebecca Daly
- VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States.,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Ellen E Lee
- VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States.,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States.,VA San Diego Healthcare System, San Diego, CA, United States
| | - Dilip V Jeste
- VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States.,Department of Psychiatry, University of California, San Diego, San Diego, CA, United States.,Department of Neurosciences, University of California, San Diego, San Diego, CA, United States
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Jeste DV, Thomas ML, Liu J, Daly RE, Tu XM, Treichler EBH, Palmer BW, Lee EE. Is spirituality a component of wisdom? Study of 1,786 adults using expanded San Diego Wisdom Scale (Jeste-Thomas Wisdom Index). J Psychiatr Res 2021; 132:174-181. [PMID: 33126011 PMCID: PMC7736537 DOI: 10.1016/j.jpsychires.2020.09.033] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 09/16/2020] [Accepted: 09/25/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Wisdom has gained increasing interest among researchers as a personality trait relevant to well-being and mental health. We previously reported development of a new 24-item San Diego Wisdom Scale (SD-WISE), with good to excellent psychometric properties, comprised of six subscales: pro-social behaviors, emotional regulation, self-reflection (insight), tolerance for divergent values (acceptance of uncertainty), decisiveness, and social advising. There is controversy about whether spirituality is a marker of wisdom. The present cross-sectional study sought to address that question by developing a new SD-WISE subscale of spirituality and examining its associations with various relevant measures. METHODS Data were collected from a national-level sample of 1,786 community-dwelling adults age 20-82 years, as part of an Amazon M-Turk cohort. Participants completed the 24-item SD-WISE along with several subscales of a commonly used Brief Multidimensional Measure of Religiousness/Spirituality, along with validated scales for well-being, resilience, happiness, depression, anxiety, loneliness, and social network. RESULTS Using latent variable models, we developed a Spirituality subscale, which demonstrated acceptable psychometric properties including a unidimensional factor structure and good reliability. Spirituality correlated positively with age and was higher in women than in men. The expanded 28-item, 7-subscale SD-WISE total score (called the Jeste-Thomas Wisdom Index or JTWI) demonstrated acceptable psychometric properties. The Spirituality subscale was positively correlated with good mental health and well-being, and negatively correlated with poor mental health. However, compared to other components of wisdom, the Spirituality factor showed weaker (i.e., small-to-medium vs. medium-to-large) association with the SD-WISE higher-order Wisdom factor (JTWI). CONCLUSION Similar to other components as well as overall wisdom, spirituality is significantly associated with better mental health and well-being, and may add to the predictive utility of the total wisdom score. Spirituality is, however, a weaker contributor to overall wisdom than components like pro-social behaviors and emotional regulation. Longitudinal studies of larger and more diverse samples are needed to explore mediation effects of these constructs on well-being and health.
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Affiliation(s)
- Dilip V Jeste
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
| | - Michael L Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, USA
| | - Jinyuan Liu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Rebecca E Daly
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA
| | - Xin M Tu
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Emily B H Treichler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; VA Desert Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, USA
| | - Barton W Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
| | - Ellen E Lee
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
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Slayday RE, Gustavson DE, Elman JA, Beck A, McEvoy LK, Tu XM, Fang B, Hauger RL, Lyons MJ, McKenzie RE, Sanderson-Cimino ME, Xian H, Kremen WS, Franz CE. Interaction between Alcohol Consumption and Apolipoprotein E (ApoE) Genotype with Cognition in Middle-Aged Men. J Int Neuropsychol Soc 2021; 27:56-68. [PMID: 32662384 PMCID: PMC7856052 DOI: 10.1017/s1355617720000570] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Heavy alcohol consumption is associated with poorer cognitive function in older adults. Although understudied in middle-aged adults, the relationship between alcohol and cognition may also be influenced by genetics such as the apolipoprotein (ApoE) ε4 allele, a risk factor for Alzheimer's disease. We examined the relationship between alcohol consumption, ApoE genotype, and cognition in middle-aged adults and hypothesized that light and/or moderate drinkers (≤2 drinks per day) would show better cognitive performance than heavy drinkers or non-drinkers. Additionally, we hypothesized that the association between alcohol use and cognitive function would differ by ApoE genotype (ε4+ vs. ε4-). METHOD Participants were 1266 men from the Vietnam Era Twin Study of Aging (VETSA; M age = 56; range 51-60) who completed a neuropsychological battery assessing seven cognitive abilities: general cognitive ability (GCA), episodic memory, processing speed, executive function, abstract reasoning, verbal fluency, and visuospatial ability. Alcohol consumption was categorized into five groups: never, former, light, moderate, and heavy. RESULTS In fully adjusted models, there was no significant main effect of alcohol consumption on cognitive functions. However, there was a significant interaction between alcohol consumption and ApoE ε4 status for GCA and episodic memory, such that the relationship of alcohol consumption and cognition was stronger in ε4 carriers. The ε4+ heavy drinking subgroup had the poorest GCA and episodic memory. CONCLUSIONS Presence of the ε4 allele may increase vulnerability to the deleterious effects of heavy alcohol consumption. Beneficial effects of light or moderate alcohol consumption were not observed.
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Affiliation(s)
- Riki E. Slayday
- Department of Psychology, San Diego State University, San
Diego, CA, USA
| | - Daniel E. Gustavson
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Asad Beck
- University of Washington, Graduate Program in Neuroscience,
Seattle, WA, USA
| | - Linda K. McEvoy
- Department of Radiology, University of California San
Diego, La Jolla, CA, USA
| | - Xin M. Tu
- Department of Family Medicine, University of California San
Diego, La Jolla, CA, USA
| | - Bin Fang
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Richard L. Hauger
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center of Excellence for Stress and Mental Health, VA San
Diego Healthcare System, San Diego, CA, USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston
University, Boston, MA, USA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston
University, Boston, MA, USA
| | - Mark E. Sanderson-Cimino
- Department of Psychology, San Diego State University, San
Diego, CA, USA
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Hong Xian
- Department of Biostatistics, St Louis University, St.
Louis, MO, USA
| | - William S. Kremen
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center of Excellence for Stress and Mental Health, VA San
Diego Healthcare System, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of
California San Diego, La Jolla CA, USA
| | - Carol E. Franz
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center for Behavior Genetics of Aging, University of
California San Diego, La Jolla CA, USA
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Eglit GM, Elman JA, Panizzon MS, Sanderson‐Cimino ME, Williams ME, Dale AM, Eyler LT, Fennema‐Notestine C, Gillespie NA, Gustavson DE, Hatton SN, Hauger RL, Jak AJ, Logue MW, McEvoy LK, McKenzie R, Neale MC, Puckett OK, Reynolds CA, Toomey R, Tu XM, Whitsell N, Xian H, Lyons MJ, Franz CE, Kremen WS. Paradoxical cognitive reserve: Cognitive trajectories from earlier to later adulthood. Alzheimers Dement 2020. [DOI: 10.1002/alz.047686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Graham M.L. Eglit
- Center for Behavior Genetics of Aging University of California San Diego La Jolla CA USA
- Department of Psychiatry University of California San Diego La Jolla CA USA
- Veterans Affairs San Diego Healthcare System San Diego CA USA
| | | | | | | | - McKenna E. Williams
- SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San Diego CA USA
| | | | | | | | | | | | | | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
| | | | | | | | | | | | | | | | - Xin M. Tu
- University of California San Diego La Jolla CA USA
| | | | - Hong Xian
- St. Louis University St. Louis MO USA
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Kremen WS, Sanderson‐Cimino ME, Elman JA, Tu XM, Gross AL, Panizzon MS, Eglit GM, Jak AJ, Edmonds EC, Thomas KR, Eppig JS, Williams ME, Bondi MW, Lyons MJ, Franz CE. Accounting for cognitive practice effects results in earlier detection and more accurate diagnosis of MCI: Biomarker confirmation. Alzheimers Dement 2020. [DOI: 10.1002/alz.044883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- William S. Kremen
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego La Jolla CA USA
| | | | | | - Xin M. Tu
- University of California San Diego La Jolla CA USA
| | - Alden L. Gross
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
| | | | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
| | | | | | - Joel S. Eppig
- University of California San Diego La Jolla CA USA
- San Diego State University San Diego CA USA
| | - McKenna E. Williams
- SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San Diego CA USA
| | - Mark W. Bondi
- University of California, San Diego, School of Medicine San Diego CA USA
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