Association of Changes in Cerebral and Hypothalamic Structure With Sleep Dysfunction in Patients With Genetic Frontotemporal Dementia
Abstract
Background and Objectives
Sleep dysfunction is common in patients with neurodegenerative disorders; however, its neural underpinnings remain poorly characterized in genetic frontotemporal dementia (FTD). Hypothalamic nuclei important for sleep regulation may be related to this dysfunction. Thus, we examined changes in hypothalamic structure across the lifespan in patients with genetic FTD and whether these changes related to sleep dysfunction.
Methods
Data from the observational multisite Genetic Frontotemporal Dementia Initiative (GENFI) study were used. GENFI participants were adult members of a family with known pathogenic variants in the microtubule-associated protein tau (MAPT) or progranulin (GRN) genes or an expansion in the chromosome 9 open reading frame 72 (C9orf72) gene. Family members without a pathogenic variant served as controls. GENFI participants were followed annually, with up to 7 visits, and underwent clinical characterization, neuropsychological testing, biological sampling, and brain MRI. For our analyses, participants were included if they had at least 1 T1-weighted structural MRI scan available. Linear mixed-effect models were used to examine changes in sleep dysfunction, measured using the Cambridge Behavioural Inventory-Revised sleep subscale, volumetric changes in hypothalamic regions, and the associations between cortical and hypothalamic atrophy and sleep dysfunction.
Results
Participants included 491 adults with pathogenic genetic variants of FTD (27.9% symptomatic; median age: 49.4 years, 56.4%F) and 321 controls (median age: 44.2 years, 57.3%F). Pathogenic variant carriers showed greater sleep dysfunction across the adult lifespan (β = [0.25–0.34], q < 0.005) with MAPT carriers alone showing presymptomatic sleep changes (β = 0.34, q = 0.005). Cortical thinning in frontal and parietal regions was associated with greater sleep disturbances in C9orf72 and GRN carriers (q < 0.05). MAPT carriers showed consistently significant volume loss over time across all sleep-relevant hypothalamic subunits (β = [−0.56 to −0.39], q < 0.005), and reduced volumes in these subunits were related to increased sleep dysfunction (β = [−0.20 to −0.16], q < 0.05).
Discussion
These findings suggest that sleep dysfunction in patients with genetic FTD may be attributable to atrophy in sleep-relevant hypothalamic subunits, with the most severe and consistent deficits observed in MAPT carriers. While biologically plausible, our statistical approach cannot confirm a causal link between atrophy and sleep disturbances.
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References
1.
McCarter SJ, St Louis EK, Boeve BF. Sleep disturbances in frontotemporal dementia. Curr Neurol Neurosci Rep. 2016. 16(9):85.
2.
Scullin MK, Bliwise DL. Sleep, cognition, and normal aging: integrating a half century of multidisciplinary research. Perspect Psychol Sci. 2015;10(1):97-137.
3.
Merrilees J, Hubbard E, Mastick J, Miller BL, Dowling GA. Sleep in persons with frontotemporal dementia and their family caregivers. Nurs Res. 2014;63(2):129-136.
4.
Greaves CV, Rohrer JD. An update on genetic frontotemporal dementia. J Neurol. 2019;266(8):2075-2086.
5.
Gemignani A, Pietrini P, Murrell JR, et al. Slow wave and rem sleep mechanisms are differently altered in hereditary pick disease associated with the TAU G389R mutation. Arch Ital Biol. 2005;143(1):65-79.
6.
Koss DJ, Robinson L, Drever BD, et al. Mutant Tau knock-in mice display frontotemporal dementia relevant behaviour and histopathology. Neurobiol Dis. 2016;91:105-123.
7.
Tavares TP, Mitchell DGV, Coleman KK, et al. Early symptoms in symptomatic and preclinical genetic frontotemporal lobar degeneration. J Neurol Neurosurg Psychiatry. 2020;91(9):975-984.
8.
Daoud H, Postuma RB, Bourassa CV, et al. C9orf72 repeat expansions in rapid eye movement sleep behaviour disorder. Can J Neurol Sci. 2014;41(6):759-762.
9.
Sani TP, Bond RL, Marshall CR, et al. Sleep symptoms in syndromes of frontotemporal dementia and Alzheimer's disease: a proof-of-principle behavioural study. eNeurologicalSci. 2019;17:100212.
10.
Saper CB, Lowell BB. The hypothalamus. Curr Biol. 2014;24(23):R1111-R1116.
11.
Moore RY. Suprachiasmatic nucleus in sleep-wake regulation. Sleep Med. 2007;8(suppl 3):27-33.
12.
Yamashita T, Yamanaka A. Lateral hypothalamic circuits for sleep-wake control. Curr Opin Neurobiol. 2017;44:94-100.
13.
Tsunematsu T, Ueno T, Tabuchi S, et al. Optogenetic manipulation of activity and temporally controlled cell-specific ablation reveal a role for MCH neurons in sleep/wake regulation. J Neurosci. 2014;34(20):6896-6909.
14.
Jego S, Glasgow SD, Herrera CG, et al. Optogenetic identification of a rapid eye movement sleep modulatory circuit in the hypothalamus. Nat Neurosci. 2013;16(11):1637-1643.
15.
Arrigoni E, Fuller PM. The sleep-promoting ventrolateral preoptic nucleus: what have we learned over the past 25 years? Int J Mol Sci. 2022;23(6):2905.
16.
Van Erum J, Van Dam D, De Deyn PP. Sleep and Alzheimer's disease: a pivotal role for the suprachiasmatic nucleus. Sleep Med Rev. 2018;40:17-27.
17.
Kalaitzakis ME, Gentleman SM, Pearce RKB. Disturbed sleep in Parkinson's disease: anatomical and pathological correlates. Neuropathol Appl Neurobiol. 2013;39(6):644-653.
18.
Anderson KN, Hatfield C, Kipps C, Hastings M, Hodges JR. Disrupted sleep and circadian patterns in frontotemporal dementia. Eur J Neurol. 2009;16(3):317-323.
19.
Çoban A, Bilgiç B, Lohmann E, et al. Reduced orexin-A levels in frontotemporal dementia: possible association with sleep disturbance. Am J Alzheimers Dis other Demen. 2013;28(6):606-611.
20.
Liguori C, Romigi A, Mercuri NB, et al. Cerebrospinal-fluid orexin levels and daytime somnolence in frontotemporal dementia. J Neurol. 2014;261(9):1832-1836.
21.
Bussy A, Levy JP, Best T, et al. Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia. Hum Brain Mapp. 2023;44(7):2684-2700.
22.
The Genetic Frontotemporal Initiative. Accessed June 20, 2024. genfi.org
23.
Rohrer JD, Nicholas JM, Cash DM, et al. Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis. Lancet Neurol. 2015;14(3):253-262.
24.
Wear HJ, Wedderburn CJ, Mioshi E, et al. The Cambridge behavioural inventory revised. Demen Neuropsychologia. 2008;2(2):102-107.
25.
Reuter M, Tisdall MD, Qureshi A, Buckner RL, van der Kouwe AJW, Fischl B. Head motion during MRI acquisition reduces gray matter volume and thickness estimates. Neuroimage. 2015;107:107-115.
26.
Bedford SA, Park MTM, Devenyi GA, et al. Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder. Mol Psychiatry. 2020;25(3):614-628.
27.
Computational Brain Anatomy Laboratory. Motion quality control (QC) manual. Accessed June 20, 2024. github.com/CoBrALab/documentation/wiki/Motion-Quality-Control-(QC)-Manual
28.
Computational Brain Anatomy Laboratory. Accessed June 20, 2024. minc-bpipe-library. github.com/CoBrALab/minc-bpipe-library
29.
Tustison NJ, Avants BB, Cook PA, et al. N4ITK: improved N3 bias correction. IEEE Trans Med Imaging. 2010;29(6):1310-1320.
30.
Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr. 1994;18(2):192-205.
31.
Dadar M, Fonov VS, Collins DL, Alzheimer’s Disease Neuroimaging Initiative. A comparison of publicly available linear MRI stereotaxic registration techniques. Neuroimage. 2018;174:191-200.
32.
Eskildsen SF, Coupé P, Fonov V, et al. BEaST: brain extraction based on nonlocal segmentation technique. Neuroimage. 2012;59(3):2362-2373.
33.
McConnell Brain Imaging Centre. Accessed June 20, 2024. CIVET 2.1.1 bic.mni.mcgill.ca/ServicesSoftware/CIVET-2-1-0-Introduction
34.
Billot B, Bocchetta M, Todd E, Dalca AV, Rohrer JD, Iglesias JE. Automated segmentation of the hypothalamus and associated subunits in brain MRI. Neuroimage. 2020;223:117287.
35.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B: Stat Methodol. 1995;57(1):289-300.
36.
Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res. 2001;125(1‐-2):279-284.
37.
The Genetic Frontotemporal Initiative. GENFI—contact us. Accessed June 20, 2024. genfi.org/contact-us-2/
38.
Bocchetta M, Todd EG, Peakman G, et al. Differential early subcortical involvement in genetic FTD within the GENFI cohort. Neuroimage Clin. 2021;30:102646.
39.
Bocchetta M, Gordon E, Manning E, et al. Detailed volumetric analysis of the hypothalamus in behavioral variant frontotemporal dementia. J Neurol. 2015;262(12):2635-2642.
40.
Piguet O, Petersén A, Yin Ka Lam B, et al. Eating and hypothalamus changes in behavioral-variant frontotemporal dementia. Ann Neurol. 2011;69(2):312-319.
41.
Sexton CE, Storsve AB, Walhovd KB, Johansen-Berg H, Fjell AM. Poor sleep quality is associated with increased cortical atrophy in community-dwelling adults. Neurology. 2014;83(11):967-973.
42.
Mander BA, Rao V, Lu B, et al. Prefrontal atrophy, disrupted NREM slow waves and impaired hippocampal-dependent memory in aging. Nat Neurosci. 2013;16(3):357-364.
43.
Ahmed MR, Halliday G, Hodges RJ. Hypothalamic symptoms of frontotemporal dementia disorders. Handb Clin Neurol. 2021;182:269-280.
44.
Warren JD, Clark CN. A new hypnic paradigm of neurodegenerative proteinopathies. Sleep Med. 2017;32:282-283.
45.
Hwang YT, Piguet O, Hodges JR, Grunstein R, Burrell JR. Sleep and orexin: a new paradigm for understanding behavioural-variant frontotemporal dementia? Sleep Med Rev. 2020;54:101361.
46.
Khoury R, Liu Y, Sheheryar Q, Grossberg GT. Pharmacotherapy for frontotemporal dementia. CNS Drugs. 2021;35(4):425-438.
47.
Moore KM, Nicholas J, Grossman M, et al. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study. Lancet Neurol. 2020;19(2):145-156.
48.
Hofman MA, Swaab DF. The human hypothalamus: comparative morphometry and photoperiodic influences. Prog Brain Res. 1992;93:133-149.
49.
Vaou OE, Lin SH, Branson C, Auerbach S. Sleep and dementia. Curr Sleep Med Rep. 2018;4(2):134-142.
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© 2024 American Academy of Neurology.
Publication History
Received: March 19, 2024
Accepted: October 2, 2024
Published online: November 11, 2024
Published in print: December 10, 2024
Disclosure
M. Bocchetta is supported by a Fellowship award from the Alzheimer's Society, UK (AS-JF-19a-004-517), and the UK Dementia Research Institute which receives its funding from DRI Ltd., funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. J.D. Rohrer is an MRC Clinician Scientist (MR/M008525/1) and has received funding from the NIHR Rare Diseases Translational Research Collaboration (BRC149/NS/MH), the Bluefield Project and the Association for Frontotemporal Degeneration. The other authors report no disclosures. Go to Neurology.org/N for full disclosures.
Study Funding
This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains for Healthy Lives initiative. GENFI was also supported by the MRC UK GENFI grant (MR/M023664/1), the Italian Ministry of Health (CoEN015 and Ricerca Corrente), the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, the Alzheimer's Society grant (AS-PG-16-007), the Bluefield Project and the JPND GENFIPROX grant (2019–02248). This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy–ID 390857198). Several authors of this publication (JCvS, MS, RSV, AD, MO, JDR) are members of the European Reference Network for Rare Neurologic Diseases (ERN-RND)—Project ID No 739510. This work was also funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC2145 SyNergy–ID 390857198), and by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014).
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