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Published in: Journal of Translational Medicine 1/2022

Open Access 01-12-2022 | Alzheimer's Disease | Research

Body mass index, genetic susceptibility, and Alzheimer's disease: a longitudinal study based on 475,813 participants from the UK Biobank

Authors: Shiqi Yuan, Wentao Wu, Wen Ma, Xiaxuan Huang, Tao Huang, MIn Peng, Anding Xu, Jun Lyu

Published in: Journal of Translational Medicine | Issue 1/2022

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Abstract

Background

The association between body mass index (BMI) and Alzheimer's disease (AD) remains controversial. Genetic and environmental factors are now considered contributors to AD risk. However, little is known about the potential interaction between genetic risk and BMI on AD risk.

Objective

To study the causal relationship between BMI and AD, and the potential interaction between AD genetic risk and BMI on AD risk.

Methods and Results

Using the UK Biobank database, 475,813 participants were selected for an average follow-up time of more than 10 years. Main findings: 1) there was a nonlinear relationship between BMI and AD risk in participants aged 60 years or older (p for non-linear < 0.001), but not in participants aged 37–59 years (p for non-linear = 0.717) using restricted cubic splines; 2) for participants aged 60 years and older, compared with the BMI (23–30 kg/m2) group, the BMI (< 23 kg/m2) group was associated with a higher AD risk (HR = 1.585; 95% CI 1.304–1.928, p < 0.001) and the BMI (> 30 kg/m2) group was associated with a lower AD risk (HR = 0.741; 95% CI 0.618–0.888, p < 0.01) analyzed using the Cox proportional risk model; 3) participants with a combination of high AD genetic risk score (AD-GRS) and BMI (< 23 kg/m2) were associated with the highest AD risk (HR = 3.034; 95% CI 2.057–4.477, p < 0.001). In addition, compared with the BMI (< 23 kg/m2), the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD-GRS; 4) there was a reverse causality between BMI and AD when analyzed using bidirectional Mendelian randomization (MR).

Conclusion

There was a reverse causality between BMI and AD analyzed using MR. For participants aged 60 years and older, the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD genetic risk. BMI (23–30 kg/m2) may be a potential intervention for AD.
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Literature
1.
go back to reference Groot C, Hooghiemstra AM, Raijmakers PG, van Berckel BN, Scheltens P, Scherder EJ, et al. The effect of physical activity on cognitive function in patients with dementia: a meta-analysis of randomized control trials. Ageing Res Rev. 2016;25:13–23.PubMedCrossRef Groot C, Hooghiemstra AM, Raijmakers PG, van Berckel BN, Scheltens P, Scherder EJ, et al. The effect of physical activity on cognitive function in patients with dementia: a meta-analysis of randomized control trials. Ageing Res Rev. 2016;25:13–23.PubMedCrossRef
2.
go back to reference Winblad B, Amouyel P, Andrieu S, Ballard C, Brayne C, Brodaty H, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol. 2016;15:455–532.PubMedCrossRef Winblad B, Amouyel P, Andrieu S, Ballard C, Brayne C, Brodaty H, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol. 2016;15:455–532.PubMedCrossRef
5.
go back to reference Yuan S, Li H, Yang C, Xie W, Wang Y, Zhang J, et al. DHA attenuates Abeta-induced necroptosis through the RIPK1/RIPK3 signaling pathway in THP-1 monocytes. Biomed Pharmacother. 2020;126: 110102.PubMedCrossRef Yuan S, Li H, Yang C, Xie W, Wang Y, Zhang J, et al. DHA attenuates Abeta-induced necroptosis through the RIPK1/RIPK3 signaling pathway in THP-1 monocytes. Biomed Pharmacother. 2020;126: 110102.PubMedCrossRef
6.
go back to reference Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med. 2011;1: a6189.CrossRef Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med. 2011;1: a6189.CrossRef
7.
go back to reference Zusso M, Barbierato M, Facci L, Skaper SD, Giusti P. Neuroepigenetics and Alzheimer’s Disease: an Update. J ALZHEIMERS DIS. 2018;64:671–88.PubMedCrossRef Zusso M, Barbierato M, Facci L, Skaper SD, Giusti P. Neuroepigenetics and Alzheimer’s Disease: an Update. J ALZHEIMERS DIS. 2018;64:671–88.PubMedCrossRef
8.
go back to reference Dunn AR, O’Connell K, Kaczorowski CC. Gene-by-environment interactions in Alzheimer’s disease and Parkinson’s disease. Neurosci Biobehav Rev. 2019;103:73–80.PubMedPubMedCentralCrossRef Dunn AR, O’Connell K, Kaczorowski CC. Gene-by-environment interactions in Alzheimer’s disease and Parkinson’s disease. Neurosci Biobehav Rev. 2019;103:73–80.PubMedPubMedCentralCrossRef
10.
go back to reference Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. Circulation. 2019;140:e596-646.PubMedPubMedCentral Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. Circulation. 2019;140:e596-646.PubMedPubMedCentral
11.
go back to reference Mariscalco G, Wozniak MJ, Dawson AG, Serraino GF, Porter R, Nath M, et al. Body mass index and mortality among adults undergoing cardiac surgery: a nationwide study with a systematic review and meta-analysis. Circulation. 2017;135:850–63.PubMedCrossRef Mariscalco G, Wozniak MJ, Dawson AG, Serraino GF, Porter R, Nath M, et al. Body mass index and mortality among adults undergoing cardiac surgery: a nationwide study with a systematic review and meta-analysis. Circulation. 2017;135:850–63.PubMedCrossRef
12.
go back to reference Qin B, Yang M, Fu H, Ma N, Wei T, Tang Q, et al. Body mass index and the risk of rheumatoid arthritis: a systematic review and dose-response meta-analysis. Arthritis Res Ther. 2015;17:86.PubMedPubMedCentralCrossRef Qin B, Yang M, Fu H, Ma N, Wei T, Tang Q, et al. Body mass index and the risk of rheumatoid arthritis: a systematic review and dose-response meta-analysis. Arthritis Res Ther. 2015;17:86.PubMedPubMedCentralCrossRef
13.
go back to reference Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371:569–78.PubMedCrossRef Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371:569–78.PubMedCrossRef
14.
go back to reference Nordestgaard LT, Tybjaerg-Hansen A, Nordestgaard BG, Frikke-Schmidt R. Body mass index and risk of Alzheimer’s disease: a mendelian randomization study of 399,536 individuals. J Clin Endocrinol Metab. 2017;102:2310–20.PubMedPubMedCentralCrossRef Nordestgaard LT, Tybjaerg-Hansen A, Nordestgaard BG, Frikke-Schmidt R. Body mass index and risk of Alzheimer’s disease: a mendelian randomization study of 399,536 individuals. J Clin Endocrinol Metab. 2017;102:2310–20.PubMedPubMedCentralCrossRef
15.
go back to reference Loef M, Walach H. Midlife obesity and dementia: meta-analysis and adjusted forecast of dementia prevalence in the United States and China. Obesity (Silver Spring). 2013;21:E51–5.CrossRef Loef M, Walach H. Midlife obesity and dementia: meta-analysis and adjusted forecast of dementia prevalence in the United States and China. Obesity (Silver Spring). 2013;21:E51–5.CrossRef
16.
go back to reference Fitzpatrick AL, Kuller LH, Lopez OL, Diehr P, O’Meara ES, Longstreth WJ, et al. Midlife and late-life obesity and the risk of dementia: cardiovascular health study. Arch Neurol. 2009;66:336–42.PubMedPubMedCentralCrossRef Fitzpatrick AL, Kuller LH, Lopez OL, Diehr P, O’Meara ES, Longstreth WJ, et al. Midlife and late-life obesity and the risk of dementia: cardiovascular health study. Arch Neurol. 2009;66:336–42.PubMedPubMedCentralCrossRef
17.
go back to reference Dahl AK, Lopponen M, Isoaho R, Berg S, Kivela SL. Overweight and obesity in old age are not associated with greater dementia risk. J Am Geriatr Soc. 2008;56:2261–6.PubMedCrossRef Dahl AK, Lopponen M, Isoaho R, Berg S, Kivela SL. Overweight and obesity in old age are not associated with greater dementia risk. J Am Geriatr Soc. 2008;56:2261–6.PubMedCrossRef
18.
go back to reference Qizilbash N, Gregson J, Johnson ME, Pearce N, Douglas I, Wing K, et al. BMI and risk of dementia in two million people over two decades: a retrospective cohort study. Lancet Diabetes Endocrinol. 2015;3:431–6.PubMedCrossRef Qizilbash N, Gregson J, Johnson ME, Pearce N, Douglas I, Wing K, et al. BMI and risk of dementia in two million people over two decades: a retrospective cohort study. Lancet Diabetes Endocrinol. 2015;3:431–6.PubMedCrossRef
19.
go back to reference Kumari M, Holmes MV, Dale CE, Hubacek JA, Palmer TM, Pikhart H, et al. Alcohol consumption and cognitive performance: a Mendelian randomization study. Addiction. 2014;109:1462–71.PubMedPubMedCentralCrossRef Kumari M, Holmes MV, Dale CE, Hubacek JA, Palmer TM, Pikhart H, et al. Alcohol consumption and cognitive performance: a Mendelian randomization study. Addiction. 2014;109:1462–71.PubMedPubMedCentralCrossRef
20.
go back to reference Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1–22.PubMedCrossRef Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1–22.PubMedCrossRef
21.
go back to reference Mukherjee S, Walter S, Kauwe J, Saykin AJ, Bennett DA, Larson EB, et al. Genetically predicted body mass index and Alzheimer’s disease-related phenotypes in three large samples: Mendelian randomization analyses. Alzheimers Dement. 2015;11:1439–51.PubMedPubMedCentralCrossRef Mukherjee S, Walter S, Kauwe J, Saykin AJ, Bennett DA, Larson EB, et al. Genetically predicted body mass index and Alzheimer’s disease-related phenotypes in three large samples: Mendelian randomization analyses. Alzheimers Dement. 2015;11:1439–51.PubMedPubMedCentralCrossRef
22.
go back to reference Davey SG, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89-98.CrossRef Davey SG, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89-98.CrossRef
23.
go back to reference Wu WT, Li YJ, Feng AZ, Li L, Huang T, Xu AD, et al. Data mining in clinical big data: the frequently used databases, steps, and methodological models. Mil Med Res. 2021;8:44.PubMedPubMedCentral Wu WT, Li YJ, Feng AZ, Li L, Huang T, Xu AD, et al. Data mining in clinical big data: the frequently used databases, steps, and methodological models. Mil Med Res. 2021;8:44.PubMedPubMedCentral
24.
go back to reference Yang J, Li Y, Liu Q, Li L, Feng A, Wang T, et al. Brief introduction of medical database and data mining technology in big data era. J Evid Based Med. 2020;13:57–69.PubMedPubMedCentralCrossRef Yang J, Li Y, Liu Q, Li L, Feng A, Wang T, et al. Brief introduction of medical database and data mining technology in big data era. J Evid Based Med. 2020;13:57–69.PubMedPubMedCentralCrossRef
25.
go back to reference Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. Plos Med. 2015;12: e1001779.PubMedPubMedCentralCrossRef Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. Plos Med. 2015;12: e1001779.PubMedPubMedCentralCrossRef
26.
go back to reference Tao F, Cao Z, Jiang Y, Fan N, Xu F, Yang H, et al. Associations of sleep duration and quality with incident cardiovascular disease, cancer, and mortality: a prospective cohort study of 407,500 UK biobank participants. Sleep Med. 2021;81:401–9.PubMedCrossRef Tao F, Cao Z, Jiang Y, Fan N, Xu F, Yang H, et al. Associations of sleep duration and quality with incident cardiovascular disease, cancer, and mortality: a prospective cohort study of 407,500 UK biobank participants. Sleep Med. 2021;81:401–9.PubMedCrossRef
27.
go back to reference Petermann-Rocha F, Parra-Soto S, Gray S, Anderson J, Welsh P, Gill J, et al. Vegetarians, fish, poultry, and meat-eaters: who has higher risk of cardiovascular disease incidence and mortality? A prospective study from UK Biobank. Eur Heart J. 2021;42:1136–43.PubMedCrossRef Petermann-Rocha F, Parra-Soto S, Gray S, Anderson J, Welsh P, Gill J, et al. Vegetarians, fish, poultry, and meat-eaters: who has higher risk of cardiovascular disease incidence and mortality? A prospective study from UK Biobank. Eur Heart J. 2021;42:1136–43.PubMedCrossRef
28.
go back to reference Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.PubMedPubMedCentralCrossRef Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.PubMedPubMedCentralCrossRef
29.
go back to reference Leng Y, Ackley SF, Glymour MM, Yaffe K, Brenowitz WD. Genetic risk of Alzheimer’s disease and sleep duration in non-demented elders. Ann Neurol. 2021;89:177–81.PubMedCrossRef Leng Y, Ackley SF, Glymour MM, Yaffe K, Brenowitz WD. Genetic risk of Alzheimer’s disease and sleep duration in non-demented elders. Ann Neurol. 2021;89:177–81.PubMedCrossRef
30.
go back to reference Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat Genet. 2019;51:404–13.PubMedPubMedCentralCrossRef Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat Genet. 2019;51:404–13.PubMedPubMedCentralCrossRef
31.
32.
go back to reference Fan M, Sun D, Zhou T, Heianza Y, Lv J, Li L, et al. Sleep patterns, genetic susceptibility, and incident cardiovascular disease: a prospective study of 385 292 UK biobank participants. Eur Heart J. 2020;41:1182–9.PubMedCrossRef Fan M, Sun D, Zhou T, Heianza Y, Lv J, Li L, et al. Sleep patterns, genetic susceptibility, and incident cardiovascular disease: a prospective study of 385 292 UK biobank participants. Eur Heart J. 2020;41:1182–9.PubMedCrossRef
33.
go back to reference Timpson NJ, Nordestgaard BG, Harbord RM, Zacho J, Frayling TM, Tybjaerg-Hansen A, et al. C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization. Int J Obes (Lond). 2011;35:300–8.CrossRef Timpson NJ, Nordestgaard BG, Harbord RM, Zacho J, Frayling TM, Tybjaerg-Hansen A, et al. C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization. Int J Obes (Lond). 2011;35:300–8.CrossRef
34.
go back to reference Zheng J, Baird D, Borges MC, Bowden J, Hemani G, Haycock P, et al. Recent developments in Mendelian randomization studies. Curr Epidemiol Rep. 2017;4:330–45.PubMedPubMedCentralCrossRef Zheng J, Baird D, Borges MC, Bowden J, Hemani G, Haycock P, et al. Recent developments in Mendelian randomization studies. Curr Epidemiol Rep. 2017;4:330–45.PubMedPubMedCentralCrossRef
35.
go back to reference Sproviero W, Winchester L, Newby D, Fernandes M, Shi L, Goodday SM, et al. High blood pressure and risk of dementia: a two-sample Mendelian randomization study in the UK Biobank. Biol Psychiatry. 2021;89:817–24.PubMedCrossRef Sproviero W, Winchester L, Newby D, Fernandes M, Shi L, Goodday SM, et al. High blood pressure and risk of dementia: a two-sample Mendelian randomization study in the UK Biobank. Biol Psychiatry. 2021;89:817–24.PubMedCrossRef
38.
go back to reference Anstey KJ, Cherbuin N, Budge M, Young J. Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes Rev. 2011;12:e426–37.PubMedCrossRef Anstey KJ, Cherbuin N, Budge M, Young J. Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes Rev. 2011;12:e426–37.PubMedCrossRef
39.
go back to reference Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet. 2011;377:557–67.PubMedPubMedCentralCrossRef Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet. 2011;377:557–67.PubMedPubMedCentralCrossRef
40.
go back to reference Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the lancet commission. Lancet. 2020;396:413–46.PubMedPubMedCentralCrossRef Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the lancet commission. Lancet. 2020;396:413–46.PubMedPubMedCentralCrossRef
41.
go back to reference Burns JM, Johnson DK, Watts A, Swerdlow RH, Brooks WM. Reduced lean mass in early Alzheimer disease and its association with brain atrophy. Arch Neurol. 2010;67:428–33.PubMedPubMedCentralCrossRef Burns JM, Johnson DK, Watts A, Swerdlow RH, Brooks WM. Reduced lean mass in early Alzheimer disease and its association with brain atrophy. Arch Neurol. 2010;67:428–33.PubMedPubMedCentralCrossRef
42.
go back to reference Loskutova N, Honea RA, Brooks WM, Burns JM. Reduced limbic and hypothalamic volumes correlate with bone density in early Alzheimer’s disease. J Alzheimers Dis. 2010;20:313–22.PubMedPubMedCentralCrossRef Loskutova N, Honea RA, Brooks WM, Burns JM. Reduced limbic and hypothalamic volumes correlate with bone density in early Alzheimer’s disease. J Alzheimers Dis. 2010;20:313–22.PubMedPubMedCentralCrossRef
43.
go back to reference Baumgartner RN, Waters DL, Gallagher D, Morley JE, Garry PJ. Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev. 1999;107:123–36.PubMedCrossRef Baumgartner RN, Waters DL, Gallagher D, Morley JE, Garry PJ. Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev. 1999;107:123–36.PubMedCrossRef
46.
go back to reference Mun YS, Park HK, Kim J, Yeom J, Kim GH, Chun MY, et al. Association between body mass index and cognitive function in mild cognitive impairment regardless of APOE epsilon4 status. Dement Neurocogn Disord. 2022;21:30–41.PubMedPubMedCentralCrossRef Mun YS, Park HK, Kim J, Yeom J, Kim GH, Chun MY, et al. Association between body mass index and cognitive function in mild cognitive impairment regardless of APOE epsilon4 status. Dement Neurocogn Disord. 2022;21:30–41.PubMedPubMedCentralCrossRef
47.
go back to reference Blautzik J, Kotz S, Brendel M, Sauerbeck J, Vettermann F, Winter Y, et al. Relationship between body mass index, ApoE4 status, and PET-based amyloid and neurodegeneration markers in amyloid-positive subjects with normal cognition or mild cognitive impairment. J Alzheimers Dis. 2018;65:781–91.PubMedCrossRef Blautzik J, Kotz S, Brendel M, Sauerbeck J, Vettermann F, Winter Y, et al. Relationship between body mass index, ApoE4 status, and PET-based amyloid and neurodegeneration markers in amyloid-positive subjects with normal cognition or mild cognitive impairment. J Alzheimers Dis. 2018;65:781–91.PubMedCrossRef
48.
go back to reference Juhasz A, Katona E, Csongradi E, Paragh G. The regulation of body mass and its relation to the development of obesity. Orv Hetil. 2007;148:1827–36.PubMedCrossRef Juhasz A, Katona E, Csongradi E, Paragh G. The regulation of body mass and its relation to the development of obesity. Orv Hetil. 2007;148:1827–36.PubMedCrossRef
50.
52.
go back to reference Jian M, Kwan JS, Bunting M, Ng RC, Chan KH. Adiponectin suppresses amyloid-beta oligomer (AbetaO)-induced inflammatory response of microglia via AdipoR1-AMPK-NF-kappaB signaling pathway. J Neuroinflammation. 2019;16:110.PubMedPubMedCentralCrossRef Jian M, Kwan JS, Bunting M, Ng RC, Chan KH. Adiponectin suppresses amyloid-beta oligomer (AbetaO)-induced inflammatory response of microglia via AdipoR1-AMPK-NF-kappaB signaling pathway. J Neuroinflammation. 2019;16:110.PubMedPubMedCentralCrossRef
53.
go back to reference Song J, Choi SM, Kim BC. Adiponectin regulates the polarization and function of microglia via PPAR-gamma signaling under amyloid beta toxicity. Front Cell Neurosci. 2017;11:64.PubMedPubMedCentral Song J, Choi SM, Kim BC. Adiponectin regulates the polarization and function of microglia via PPAR-gamma signaling under amyloid beta toxicity. Front Cell Neurosci. 2017;11:64.PubMedPubMedCentral
54.
go back to reference Ng RC, Jian M, Ma OK, Bunting M, Kwan JS, Zhou GJ, et al. Chronic oral administration of adipoRon reverses cognitive impairments and ameliorates neuropathology in an Alzheimer’s disease mouse model. Mol Psychiatry. 2021;26:5669–89.PubMedCrossRef Ng RC, Jian M, Ma OK, Bunting M, Kwan JS, Zhou GJ, et al. Chronic oral administration of adipoRon reverses cognitive impairments and ameliorates neuropathology in an Alzheimer’s disease mouse model. Mol Psychiatry. 2021;26:5669–89.PubMedCrossRef
55.
go back to reference Liu B, Liu J, Shi JS. SAMP8 mice as a model of age-related cognition decline with underlying mechanisms in Alzheimer’s disease. J Alzheimers Dis. 2020;75:385–95.PubMedCrossRef Liu B, Liu J, Shi JS. SAMP8 mice as a model of age-related cognition decline with underlying mechanisms in Alzheimer’s disease. J Alzheimers Dis. 2020;75:385–95.PubMedCrossRef
56.
go back to reference Amieva H, Le Goff M, Millet X, Orgogozo JM, Peres K, Barberger-Gateau P, et al. Prodromal Alzheimer’s disease: successive emergence of the clinical symptoms. Ann Neurol. 2008;64:492–8.PubMedCrossRef Amieva H, Le Goff M, Millet X, Orgogozo JM, Peres K, Barberger-Gateau P, et al. Prodromal Alzheimer’s disease: successive emergence of the clinical symptoms. Ann Neurol. 2008;64:492–8.PubMedCrossRef
57.
go back to reference Kim MS, Kim WJ, Khera AV, Kim JY, Yon DK, Lee SW, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J. 2021;42:3388–403.PubMedPubMedCentralCrossRef Kim MS, Kim WJ, Khera AV, Kim JY, Yon DK, Lee SW, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J. 2021;42:3388–403.PubMedPubMedCentralCrossRef
Metadata
Title
Body mass index, genetic susceptibility, and Alzheimer's disease: a longitudinal study based on 475,813 participants from the UK Biobank
Authors
Shiqi Yuan
Wentao Wu
Wen Ma
Xiaxuan Huang
Tao Huang
MIn Peng
Anding Xu
Jun Lyu
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2022
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-022-03621-2

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