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Passero K, Noll JG, Verma SS, Selin C, Hall MA. Longitudinal method comparison: modeling polygenic risk for post-traumatic stress disorder over time in individuals of African and European ancestry. Front Genet 2024; 15:1203577. [PMID: 38818035 PMCID: PMC11137250 DOI: 10.3389/fgene.2024.1203577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 04/15/2024] [Indexed: 06/01/2024] Open
Abstract
Cross-sectional data allow the investigation of how genetics influence health at a single time point, but to understand how the genome impacts phenotype development, one must use repeated measures data. Ignoring the dependency inherent in repeated measures can exacerbate false positives and requires the utilization of methods other than general or generalized linear models. Many methods can accommodate longitudinal data, including the commonly used linear mixed model and generalized estimating equation, as well as the less popular fixed-effects model, cluster-robust standard error adjustment, and aggregate regression. We simulated longitudinal data and applied these five methods alongside naïve linear regression, which ignored the dependency and served as a baseline, to compare their power, false positive rate, estimation accuracy, and precision. The results showed that the naïve linear regression and fixed-effects models incurred high false positive rates when analyzing a predictor that is fixed over time, making them unviable for studying time-invariant genetic effects. The linear mixed models maintained low false positive rates and unbiased estimation. The generalized estimating equation was similar to the former in terms of power and estimation, but it had increased false positives when the sample size was low, as did cluster-robust standard error adjustment. Aggregate regression produced biased estimates when predictor effects varied over time. To show how the method choice affects downstream results, we performed longitudinal analyses in an adolescent cohort of African and European ancestry. We examined how developing post-traumatic stress symptoms were predicted by polygenic risk, traumatic events, exposure to sexual abuse, and income using four approaches-linear mixed models, generalized estimating equations, cluster-robust standard error adjustment, and aggregate regression. While the directions of effect were generally consistent, coefficient magnitudes and statistical significance differed across methods. Our in-depth comparison of longitudinal methods showed that linear mixed models and generalized estimating equations were applicable in most scenarios requiring longitudinal modeling, but no approach produced identical results even if fit to the same data. Since result discrepancies can result from methodological choices, it is crucial that researchers determine their model a priori, refrain from testing multiple approaches to obtain favorable results, and utilize as similar as possible methods when seeking to replicate results.
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Affiliation(s)
- Kristin Passero
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
| | - Jennie G. Noll
- Department of Psychology, Mount Hope Family Center, University of Rochester, Rochester, NY, United States
| | - Shefali Setia Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Claire Selin
- Center for Childhood Deafness, Language, and Learning, Boys Town National Research Hospital, Omaha, NE, United States
| | - Molly A. Hall
- Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, United States
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Tsapanou A, Ghanem A, Chapman S, Stern Y, Huey ED, Cosentino S, Louis ED. Sleep problems as predictors of cognitive decline in essential tremor: A prospective longitudinal cohort study. Sleep Med 2024; 116:13-18. [PMID: 38408421 DOI: 10.1016/j.sleep.2024.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/11/2023] [Accepted: 02/06/2024] [Indexed: 02/28/2024]
Abstract
BACKGROUND There is growing evidence that essential tremor (ET) patients are at high risk of cognitive impairment. Predictors of cognitive impairment have not been studied extensively. There is evidence from cross-sectional studies that sleep dysregulation is associated with cognitive dysfunction in ET, but longitudinal studies of the impact of sleep disruption on cognitive change have not been conducted. We investigated the extent to which sleep problems predict cognitive change in patients with ET. METHODS ET cases enrolled in a prospective, longitudinal study of cognitive performance. Sleep quality was assessed using the Pittsburg Sleep Quality Index (PSQI). Cognitive abilities across five domains (memory, executive function, attention, language, and visuospatial ability), and a global cognitive score (mean of the domains) were extracted from an extensive neuropsychological assessment. Generalized estimated equations were used to examine the association between baseline sleep problems and cognitive changes over three follow-up assessments each spaced 18 months apart. RESULTS The 188 non-demented ET cases had a mean age of 77.7 ± 9.5 years. Longer sleep latency was associated with longitudinal decline in executive function (p = 0.038), and marginally with longitudinal decline in global cognitive performance (p = 0.075). After excluding 29 cases with mild cognitive impairment, results were similar. CONCLUSION Cognitively healthy people with ET who have longer sleep latency had greater declines in executive function during prospective follow-up. Early detection of, and possibly intervention for, abnormal sleep latency may protect against certain aspects of cognitive decline in ET patients.
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Affiliation(s)
- Angeliki Tsapanou
- Cognitive Neuroscience Division, Columbia University Irving Medical Center, New York, NY, USA
| | - Ali Ghanem
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Silvia Chapman
- Cognitive Neuroscience Division, Columbia University Irving Medical Center, New York, NY, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Columbia University Irving Medical Center, New York, NY, USA
| | - Edward D Huey
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Stephanie Cosentino
- Cognitive Neuroscience Division, Columbia University Irving Medical Center, New York, NY, USA
| | - Elan D Louis
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
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Paz V, Wilcox H, Goodman M, Wang H, Garfield V, Saxena R, Dashti HS. Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.06.24302416. [PMID: 38370718 PMCID: PMC10871384 DOI: 10.1101/2024.02.06.24302416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.
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Affiliation(s)
- Valentina Paz
- Instituto de Psicología Clínica, Facultad de Psicología, Universidad de la República, Montevideo, Uruguay
- MRC Unit for Lifelong Health & Ageing, Institute of Cardiovascular Science, University College London, London, United Kingdom
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Hannah Wilcox
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Matthew Goodman
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Heming Wang
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Victoria Garfield
- MRC Unit for Lifelong Health & Ageing, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute, Cambridge, Massachusetts, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Hassan S. Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute, Cambridge, Massachusetts, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Nutrition, Harvard Medical School, Boston, Massachusetts, United States of America
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Sampatakakis SN, Mourtzi N, Charisis S, Mamalaki E, Ntanasi E, Hatzimanolis A, Ramirez A, Lambert JC, Yannakoulia M, Kosmidis MH, Dardiotis E, Hadjigeorgiou G, Sakka P, Scarmeas N. Genetic Predisposition for White Matter Hyperintensities and Risk of Mild Cognitive Impairment and Alzheimer's Disease: Results from the HELIAD Study. Curr Issues Mol Biol 2024; 46:934-947. [PMID: 38275674 PMCID: PMC10814944 DOI: 10.3390/cimb46010060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/13/2024] [Accepted: 01/19/2024] [Indexed: 01/27/2024] Open
Abstract
The present study investigated the association of genetic predisposition for white matter hyperintensities (WMHs) with incident amnestic mild cognitive impairment (aMCI) or Alzheimer's disease (AD), as well as whether such an association was influenced by age, sex, and cognitive reserve. Overall, 537 individuals without aMCI or dementia at baseline were included. Among them, 62 individuals developed aMCI/AD at follow up. Genetic propensity to WMH was estimated using a polygenic risk score for WMHs (PRS WMH). The association of PRS WMH with aMCI/AD incidence was examined using COX models. A higher PRS WMH was associated with a 47.2% higher aMCI/AD incidence (p = 0.015) in the fully adjusted model. Subgroup analyses showed significant results in the older age group, in which individuals with a higher genetic predisposition for WMHs had a 3.4-fold higher risk for developing aMCI/AD at follow up (p < 0.001), as well as in the lower cognitive reserve (CR, proxied by education years) group, in which individuals with a higher genetic predisposition for WMHs had an over 2-fold higher risk (p = 0.013). Genetic predisposition for WMHs was associated with aMCI/AD incidence, particularly in the group of participants with a low CR. Thus, CR might be a modifier in the relationship between genetic predisposition for WMHs and incident aMCI/AD.
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Affiliation(s)
- Stefanos N. Sampatakakis
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Niki Mourtzi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Sokratis Charisis
- Department of Neurology, UT Health San Antonio, San Antonio, TX 78229, USA;
| | - Eirini Mamalaki
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Eva Ntanasi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
| | - Alexandros Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50923 Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE Bonn), 53127 Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX 78229, USA
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50923 Cologne, Germany
| | - Jean-Charles Lambert
- Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liés au Vieillissement, University of Lille, 59000 Lille, France;
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, 17676 Athens, Greece;
| | - Mary H. Kosmidis
- Lab of Neuropsychology and Behavioral Neuroscience, School of Psychology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41334 Larissa, Greece;
| | | | - Paraskevi Sakka
- Athens Association of Alzheimer’s Disease and Related Disorders, 11636 Marousi, Greece;
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (E.M.); (E.N.)
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY 10027, USA
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Mourtzi N, Charisis S, Tsapanou A, Ntanasi E, Hatzimanolis A, Ramirez A, Heilmann-Heimbach S, Grenier-Boley B, Lambert JC, Yannakoulia M, Kosmidis M, Dardiotis E, Hadjigeorgiou G, Sakka P, Georgakis M, Yaakov S, Scarmeas N. Genetic propensity for cerebral amyloidosis and risk of mild cognitive impairment and Alzheimer's disease within a cognitive reserve framework. Alzheimers Dement 2023; 19:3794-3805. [PMID: 36895094 DOI: 10.1002/alz.12980] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/29/2022] [Accepted: 01/16/2023] [Indexed: 03/11/2023]
Abstract
INTRODUCTION We constructed a polygenic risk score (PRS) for β-amyloid (PRSAβ42) to proxy AD pathology and investigated its association with incident Alzheimer's disease (AD)/amnestic mild cognitive impairment (aMCI) and the influence of cognitive reserve (CR), proxied by educational years, on the relationship between PRSAβ42 and AD/aMCI risk. METHODS A total of 618 cognitive-normal participants were followed-up for 2.92 years. The association of PRSAβ42 and CR with AD/aMCI incidence was examined with COX models. Then we examined the additive interaction between PRSAβ42 and CR and the CR effect across participants with different PRSAβ42 levels. RESULTS Higher PRSAβ42 and CR were associated with a 33.9% higher risk and 8.3% less risk for AD/aMCI, respectively. An additive interaction between PRSAβ42 and CR was observed. High CR was associated with 62.6% less risk of AD/aMCI incidence only in the high-PRSAβ42 group. DISCUSSION A super-additive effect of PRSAβ42 and CR on AD/aMCI risk was observed. CR influence was evident in participants with high PRSAβ42.
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Affiliation(s)
- Niki Mourtzi
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
| | - Sokratis Charisis
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Angeliki Tsapanou
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Eva Ntanasi
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Alexandros Hatzimanolis
- Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE Bonn), Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, Texas, USA
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Benjamin Grenier-Boley
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille, France
| | - Jean-Charles Lambert
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille, France
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Mary Kosmidis
- Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
| | | | - Paraskevi Sakka
- Athens Association of Alzheimer's Disease and Related Disorders, Marousi, Greece
| | - Marios Georgakis
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Boston, Massachusetts, USA
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Stern Yaakov
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
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Zhang Y, Elgart M, Granot-Hershkovitz E, Wang H, Tarraf W, Ramos AR, Stickel AM, Zeng D, Garcia TP, Testai FD, Wassertheil-Smoller S, Isasi CR, Daviglus ML, Kaplan R, Fornage M, DeCarli C, Redline S, González HM, Sofer T. Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of Latinos. EBioMedicine 2023; 87:104393. [PMID: 36493726 PMCID: PMC9732133 DOI: 10.1016/j.ebiom.2022.104393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 11/18/2022] [Accepted: 11/18/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Sleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults. METHODS We used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value <0.05. FINDINGS Higher PRS for insomnia was associated with lower global cognitive function and higher risk of mild cognitive impairment (MCI) (OR = 1.20, 95% CI [1.06, 1.36]). Higher PRS for daytime sleepiness was also associated with increased MCI risk (OR = 1.14, 95% CI [1.02, 1.28]). Sleep duration PRS was associated with reduced MCI risk among short and normal sleepers, while among long sleepers it was associated with reduced global cognitive function and with increased MCI risk (OR = 1.40, 95% CI [1.10, 1.78]). Furthermore, adjustment of analyses for the measured sleep phenotypes and APOE-ε4 allele had minor effects on the PRS associations with the cognitive outcomes. INTERPRETATION Genetic measures underlying insomnia, daytime sleepiness, and sleep duration are associated with MCI risk. Genetic and self-reported sleep duration interact in their effect on MCI. FUNDING Described in Acknowledgments.
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Affiliation(s)
- Yuan Zhang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Michael Elgart
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Einat Granot-Hershkovitz
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Wassim Tarraf
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Alberto R Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ariana M Stickel
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Donglin Zeng
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Tanya P Garcia
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Fernando D Testai
- Department of Neurology and Rehabilitation, University of Illinois College of Medicine at Chicago, Chicago, IL, USA
| | | | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Robert Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Charles DeCarli
- Department of Neurology, Alzheimer's Disease Center, University of California, Davis, Sacramento, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hector M González
- Department of Neurosciences and Shiley-Marcos Alzheimer's Disease Center, University of California, San Diego, La Jolla, CA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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