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Egle M, Hilal S, Tuladhar AM, Pirpamer L, Bell S, Hofer E, Duering M, Wason J, Morris RG, Dichgans M, Schmidt R, Tozer DJ, Barrick TR, Chen C, de Leeuw FE, Markus HS. Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease. NEUROIMAGE: CLINICAL 2022; 35:103114. [PMID: 35908307 PMCID: PMC9421487 DOI: 10.1016/j.nicl.2022.103114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/24/2022] [Accepted: 07/10/2022] [Indexed: 11/23/2022] Open
Abstract
We were not able to identify a single optimal diffusion-weighted imaging analysis strategy across all 6 cohorts. Diffusion tensor imaging measures at baseline predicted dementia conversion in cerebral small vessel disease and mild cognitive impairment. Diffusion tensor imaging measures at baseline may be sensitive to differentiate between later vascular dementia vs Alzheimer’s disease dementia. Diffusion tensor imaging measures significantly changed over time in cohorts with cerebral small vessel disease and cohorts with mild cognitive impairment. Change in diffusion tensor imaging measures were only consistently associated with dementia conversion in severe SVD. The diffusion tensor imaging measures PSMD and DSEG required the lowest minimum sample sizes for a hypothetical clinical trial in patients with sporadic cerebral small vessel disease and mild cognitive impairment.
Background DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study’s objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity. Methods Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy. Results There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer’ s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts. Conclusion DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.
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Egle M, Hilal S, Tuladhar AM, Pirpamer L, Hofer E, Duering M, Wason J, Morris RG, Dichgans M, Schmidt R, Tozer D, Chen C, de Leeuw FE, Markus HS. Prediction of dementia using diffusion tensor MRI measures: the OPTIMAL collaboration. J Neurol Neurosurg Psychiatry 2022; 93:14-23. [PMID: 34509999 DOI: 10.1136/jnnp-2021-326571] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 08/21/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVES It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts. METHODS Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined. RESULTS The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures. CONCLUSIONS Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity.
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Koini M, Pirpamer L, Hofer E, Buchmann A, Pinter D, Ropele S, Enzinger C, Benkert P, Leppert D, Kuhle J, Schmidt R, Khalil M. Factors influencing serum neurofilament light chain levels in normal aging. Aging (Albany NY) 2021; 13:25729-25738. [PMID: 34923481 PMCID: PMC8751593 DOI: 10.18632/aging.203790] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 12/08/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Serum neurofilament light (sNfL) is a promising marker for neuro-axonal damage and it is now well known that its levels also increase with higher age. However, the effect of other determinants besides age is still poorly investigated. We therefore aimed to identify factors influencing the sNfL concentration by analysing a large set of demographical, life-style and clinical variables in a normal aging cohort. METHODS sNfL was quantified by single molecule array (Simoa) assay in 327 neurologically inconspicuous individuals (median age 67.8±10.7 years, 192 female) who participated in the Austrian Stroke Prevention Family Study (ASPS-Fam). Random forest regression analysis was used to rank the association of included variables with sNfL in the entire cohort and in age-stratified subgroups. Linear regression then served to identify factors independently influencing sNfL concentration. RESULTS Age (β=0.513, p<0.001) was by far the most important factor influencing sNfL, which was mainly driven by individuals ≥60 years. In age stratified sub-groups, body mass index (BMI) (β=-0.298, p<0.001) independently predicted sNfL in individuals aged 38-60 years. In individuals ≥60 years, age (β=0.394, p<0.001), renal function (β=0.376, p<0.001), blood volume (β=-0.198, p=0.008) and high density lipoprotein (HDL) (β=0.149, p=0.013) were associated with sNfL levels. CONCLUSIONS Age is the most important factor influencing sNfL concentrations, getting increasingly relevant in elderly people. BMI further influences sNfL levels, especially at younger age, whereas renal function gets increasingly relevant in the elderly.
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Graham SE, Clarke SL, Wu KHH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, Locke AE, Marouli E, Hwang MY, Han S, Narita A, Choudhury A, Bentley AR, Ekoru K, Verma A, Trivedi B, Martin HC, Hunt KA, Hui Q, Klarin D, Zhu X, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Ruotsalainen SE, Havulinna AS, Veturi Y, Feng Q, Rosenthal EA, Lingren T, Pacheco JA, Pendergrass SA, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Hindy G, Rasheed A, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Willemsen G, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Yao J, Manichaikul A, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Sidore C, Fiorillo E, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Thuesen BH, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Feitosa MF, Wojczynski MK, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Kember RL, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Leonard HL, Marten J, Schmidt B, Arendt M, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Ahmed M, Jackson AU, Yousri NA, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Chai X, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Hung YJ, Chen S, Liu F, Yang J, Kentistou KA, Gorski M, Brumat M, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Xue C, Zhang J, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, Lee J, van der Laan SW, Chitrala KN, Weiss S, Zimmermann ME, Lee JY, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hildalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Schwander K, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Highland HM, Young KL, Kawaguchi T, Thiery J, Bis JC, Nadkarni GN, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, Bhatti KF, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Chen YE, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Kato N, Schulze MB, Girotto G, Jung B, Böger CA, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, den Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Yajnik CS, Mercader JM, Tusié-Luna T, Aguilar-Salinas CA, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Lu F, Qu J, Hishigaki H, Lin X, März W, Parra EJ, Cruz M, Gudnason V, Tardif JC, Lettre G, 't Hart LM, Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Psaty BM, Brandslund I, Pramstaller PP, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Cucca F, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, de Geus EJC, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Justice AE, Baras A, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Thorsteinsdottir U, Stefansson K, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson P, Rotimi CN, Hazelhurst S, Ramsay M, Trembath RC, van Heel DA, Tamiya G, Yamamoto M, Kim BJ, Mohlke KL, Frayling TM, Hirschhorn JN, Kathiresan S, Boehnke M, Natarajan P, Peloso GM, Brown CD, Morris AP, Assimes TL, Deloukas P, Sun YV, Willer CJ. The power of genetic diversity in genome-wide association studies of lipids. Nature 2021; 600:675-679. [PMID: 34887591 PMCID: PMC8730582 DOI: 10.1038/s41586-021-04064-3] [Citation(s) in RCA: 327] [Impact Index Per Article: 109.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 09/27/2021] [Indexed: 01/14/2023]
Abstract
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
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Knol MJ, Pawlak MA, Lamballais S, Terzikhan N, Hofer E, Xiong Z, Klaver CCW, Pirpamer L, Vernooij MW, Ikram MA, Schmidt R, Kayser M, Evans TE, Adams HHH. Genetic architecture of orbital telorism. Hum Mol Genet 2021; 31:1531-1543. [PMID: 34791242 PMCID: PMC9071440 DOI: 10.1093/hmg/ddab334] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 11/19/2022] Open
Abstract
The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs’ centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985–0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucleotide polymorphism-based method (N = 34 130) and were unaffected by adjustment for height (model II) and intracranial volume (model III) or head width (model IV). Genome-wide association studies in 34 130 European individuals identified 56 significantly associated genomic loci (P < 5 × 10−8) across four different models of which 46 were novel for facial morphology, and overall these findings replicated in an independent sample (N = 10 115) with telorism-related horizontal facial distance measures. Genes located nearby these 56 identified genetic loci were 4.9-fold enriched for Mendelian hypotelorism and hypertelorism genes, underlining their biological relevance. This study provides novel insights into the genetic architecture underlying interocular distance in particular, and the face in general, and explores its potential for applications in a clinical setting.
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Herrmann M, Simstich S, Fauler G, Hofer E, Fritz-Petrin E, Herrmann W, Schmidt R. The relationship between plasma free fatty acids, cognitive function and structural integrity of the brain in middle-aged healthy humans. Aging (Albany NY) 2021; 13:22078-22091. [PMID: 34554925 PMCID: PMC8507298 DOI: 10.18632/aging.203573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/07/2021] [Indexed: 11/25/2022]
Abstract
Background: The cerebral composition of ω-3 and ω-6 polyunsaturated fatty acids (PUFAs) is believed to influence cognitive function and structural damage of the aging brain. However, existing data is inconsistent. Materials and Methods: This retrospective study explored the association between free plasma PUFA concentrations, cognitive function and brain structure atrophy in a well-characterized community-dwelling cohort of elderly individuals without stroke and dementia. Ten different fatty acids were analyzed in stored plasma samples from 391 non-demented elderly individuals by gas chromatography mass spectrometry. Neuropsychiatric tests capturing memory, executive function and visuopractical skills were performed in all participants. Brain atrophy was assessed by MRI in a subset of 167 individuals. Results: Higher plasma concentrations of free ω-6 PUFAs (p = 0.042), and, in particular, linoleic acid (p = 0.01), were significantly associated with lower executive function. No significant association existed between ω-3 PUFA concentrations and cognitive functioning. The volume of the frontal lobes was inversely associated with ω-6 PUFAs, whereas ω-3 PUFAs were positively related with temporal lobe volumes. All associations did not withstand correction for multiple comparisons. Conclusions: Our study suggests subtle effects of PUFA imbalances on cognition and brain structure. Yet the observed associations are weak and unlikely to be of clinical relevance. The brain regions that seem to be most sensitive to imbalances of ω-3 and ω-6 PUFAs are the frontal and temporal lobes.
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Kneihsl M, Bisping E, Scherr D, Mangge H, Fandler-Höfler S, Colonna I, Haidegger M, Eppinger S, Hofer E, Fazekas F, Enzinger C, Gattringer T. Predicting atrial fibrillation after cryptogenic stroke via a clinical risk score-a prospective observational study. Eur J Neurol 2021; 29:149-157. [PMID: 34519135 PMCID: PMC9292187 DOI: 10.1111/ene.15102] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 09/09/2021] [Indexed: 11/29/2022]
Abstract
Background and purpose Atrial fibrillation (AF) often remains undiagnosed in cryptogenic stroke (CS), mostly because of limited availability of cardiac long‐term rhythm monitoring. There is an unmet need for a pre‐selection of CS patients benefitting from such work‐up. A clinical risk score was therefore developed for the prediction of AF after CS and its performance was evaluated over 1 year of follow‐up. Methods Our proposed risk score ranges from 0 to 16 points and comprises variables known to be associated with occult AF in CS patients including age, N‐terminal pro‐brain natriuretic peptide, electrocardiographic and echocardiographic features (supraventricular premature beats, atrial runs, atrial enlargement, left ventricular ejection fraction) and brain imaging markers (multi‐territory/prior cortical infarction). All CS patients admitted to our Stroke Unit between March 2018 and August 2019 were prospectively followed for AF detection over 1 year after discharge. Results During the 1‐year follow‐up, 24 (16%) out of 150 CS patients with AF (detected via electrocardiogram controls, n = 18; loop recorder monitoring, n = 6) were diagnosed. Our predefined AF Risk Score (cutoff ≥4 points; highest Youden's index) had a sensitivity of 92% and a specificity of 67% for 1‐year prediction of AF. Notably, only two CS patients with <4 score points were diagnosed with AF later on (negative predictive value 98%). Conclusions A clinical risk score for 1‐year prediction of AF in CS with high sensitivity, reasonable specificity and excellent negative predictive value is presented. Generalizability of our score needs to be tested in external cohorts with continuous cardiac rhythm monitoring.
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Engel DC, Pirpamer L, Hofer E, Schmidt R, Brendle C. Incidental findings of typical iNPH imaging signs in asymptomatic subjects with subclinical cognitive decline. Fluids Barriers CNS 2021; 18:37. [PMID: 34391462 PMCID: PMC8364005 DOI: 10.1186/s12987-021-00268-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 07/07/2021] [Indexed: 01/15/2023] Open
Abstract
Background The etiology of idiopathic normal pressure hydrocephalus (iNPH) remains unclear. Little is known about the pre-symptomatic stage. This study aimed to investigate the association of neuropsychological data with iNPH-characteristic imaging changes compared to normal imaging and unspecific atrophy in a healthy population. Methods We extracted data from the community-dwelling Austrian Stroke Prevention Family Study (ASPS-Fam) database (2006–2010). All subjects underwent a baseline and identical follow-up examination after 3–5 years with MR imaging and an extensive neuropsychological test battery (Trail Making Test B, short physical performance balance, walking speed, memory, visuo-practical skills, composite scores of executive function and g-factor). We categorized the subjects into “iNPH”-associated, non-specific “atrophy,” and “normal” based on the rating of different radiological cerebrospinal fluid (CSF) space parameters. We noted how the categories developed over time. We assessed the association of the image categories with the neuropsychological data, different demographic, and lifestyle parameters (age, sex, education, alcohol intake, arterial hypertension, hypercholesterolemia), and the extent of white matter hyperintensities. We investigated whether neuropsychological data associated with the image categories were independent from other parameters as confounders. Results One hundred and thirteen subjects, aged 50–70 years, were examined. The imaging category “iNPH” was only present at follow-up. A third of subjects with “atrophy” at baseline changed to the category “iNPH” at follow-up. More white matter hyperintensities (WMH) were present in later “iNPH” subjects. Subjects with “iNPH” performed worse than “normal” subjects on executive function (p = 0.0118), memory (p = 0.0109), and Trail Making Test B (TMT-B. p < 0.0001). Education, alcohol intake, diabetes, arterial hypertension, and hypercholesterolemia had no effect. Age, number of females, and the extent of white matter hyperintensities were higher in “iNPH” than in “normal” subjects but did not significantly confound the neuropsychological results. Conclusions Apparent asymptomatic subjects with “iNPH” imaging characteristics presented with subclinical cognitive decline and showed worse executive function, memory, and TMT-B results than “normal” subjects. WMH seem to play a role in the etiology before ventriculomegaly. Clinical screening of individuals with incidental iNPH-characteristic imaging and conspicuous results sof these neurocognitive tests needs further validation.
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Zelzer S, Hofer E, Meinitzer A, Fritz-Petrin E, Simstich S, Goessler W, Schmidt R, Herrmann M. Association of vitamin D metabolites with cognitive function and brain atrophy in elderly individuals - the Austrian stroke prevention study. Aging (Albany NY) 2021; 13:9455-9467. [PMID: 33825696 PMCID: PMC8064143 DOI: 10.18632/aging.202930] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 03/27/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Vitamin D is a well-established regulator of calcium and phosphate metabolism that has neurotrophic and neuroprotective properties. Deficiency of vitamin D has been proposed to promote cognitive dysfunction and brain atrophy. However, existing studies provide inconsistent results. Here we aimed to investigate the association between vitamin D metabolites, cognitive function and brain atrophy in a cohort of well-characterized community-dwelling elderly individuals with normal neurological status and without history of stroke and dementia. METHODS 25(OH)D3, 25(OH)D2 and 24,25(OH)2D3 were measured by liquid-chromatography tandem mass-spectrometry in serum samples from 390 community-dwelling elderly individuals. All participants underwent thorough neuropsychiatric tests capturing memory, executive function and visuopractical skills. In 139 of these individuals, MRI of the brain was performed in order to capture neurodegenerative and vascular changes. RESULTS Total 25(OH)D (ß=0.003, 0.037), 24,25(OH)2D3 (ß=0.0456, p=0.010) and vitamin D metabolite ratio (VMR) (ß=0.0467, p=0.012) were significantly related to memory function. Adjustment for multiple testing weakened these relationships, but trends (p≤0.10) remained. 24,25(OH)2D3 and VMR showed similar trends also for visuopractical skills and global cognitive function. No significant relationships existed between vitamin D metabolites and MRI derived indices of neurodegeneration and vascular changes. Sub-group analyses of individuals with low concentrations of 25(OH)D and 24,25(OH)2D3 showed significantly worse memory function compared to individuals with normal or high concentrations. CONCLUSIONS Vitamin D deficient individuals appear to have a modest reduction of memory function without structural brain atrophy. Future studies should explore if vitamin D supplementation can improve cognitive function.
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Gorski M, Jung B, Li Y, Matias-Garcia PR, Wuttke M, Coassin S, Thio CHL, Kleber ME, Winkler TW, Wanner V, Chai JF, Chu AY, Cocca M, Feitosa MF, Ghasemi S, Hoppmann A, Horn K, Li M, Nutile T, Scholz M, Sieber KB, Teumer A, Tin A, Wang J, Tayo BO, Ahluwalia TS, Almgren P, Bakker SJL, Banas B, Bansal N, Biggs ML, Boerwinkle E, Bottinger EP, Brenner H, Carroll RJ, Chalmers J, Chee ML, Chee ML, Cheng CY, Coresh J, de Borst MH, Degenhardt F, Eckardt KU, Endlich K, Franke A, Freitag-Wolf S, Gampawar P, Gansevoort RT, Ghanbari M, Gieger C, Hamet P, Ho K, Hofer E, Holleczek B, Xian Foo VH, Hutri-Kähönen N, Hwang SJ, Ikram MA, Josyula NS, Kähönen M, Khor CC, Koenig W, Kramer H, Krämer BK, Kühnel B, Lange LA, Lehtimäki T, Lieb W, Loos RJF, Lukas MA, Lyytikäinen LP, Meisinger C, Meitinger T, Melander O, Milaneschi Y, Mishra PP, Mononen N, Mychaleckyj JC, Nadkarni GN, Nauck M, Nikus K, Ning B, Nolte IM, O'Donoghue ML, Orho-Melander M, Pendergrass SA, Penninx BWJH, Preuss MH, Psaty BM, Raffield LM, Raitakari OT, Rettig R, Rheinberger M, Rice KM, Rosenkranz AR, Rossing P, Rotter JI, Sabanayagam C, Schmidt H, Schmidt R, Schöttker B, Schulz CA, Sedaghat S, Shaffer CM, Strauch K, Szymczak S, Taylor KD, Tremblay J, Chaker L, van der Harst P, van der Most PJ, Verweij N, Völker U, Waldenberger M, Wallentin L, Waterworth DM, White HD, Wilson JG, Wong TY, Woodward M, Yang Q, Yasuda M, Yerges-Armstrong LM, Zhang Y, Snieder H, Wanner C, Böger CA, Köttgen A, Kronenberg F, Pattaro C, Heid IM. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline. Kidney Int 2021; 99:926-939. [PMID: 33137338 PMCID: PMC8010357 DOI: 10.1016/j.kint.2020.09.030] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/21/2020] [Accepted: 09/17/2020] [Indexed: 12/19/2022]
Abstract
Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.
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Gattringer T, Fandler-Höfler S, Kneihsl M, Hofer E, Köle W, Schmidt R, Tscheliessnigg KH, Frank AM, Enzinger C. Hospital admissions of acute cerebrovascular diseases during and after the first wave of the COVID-19 pandemic: a state-wide experience from Austria. J Neurol 2021; 268:3584-3588. [PMID: 33641003 PMCID: PMC7914046 DOI: 10.1007/s00415-021-10488-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 02/19/2021] [Accepted: 02/19/2021] [Indexed: 12/23/2022]
Abstract
We investigated hospital admission rates for the entire spectrum of acute cerebrovascular diseases and of recanalization treatments for ischaemic stroke (IS) in the Austrian federal state of Styria during and also after the first coronavirus disease 2019 (COVID-19) wave. We retrospectively identified all patients with transient ischaemic attack (TIA), IS and non-traumatic intracranial haemorrhage (ICH; including intracerebral, subdural and subarachnoid bleeding types) admitted to one of the 11 public hospitals in Styria (covering > 95% of inhospital cerebrovascular events in this region). Information was extracted from the electronic medical documentation network connecting all public Styrian hospitals. We analysed two periods of interest: (1) three peak months of the first COVID-19 wave (March-May 2020), and (2) three recovery months thereafter (June-August 2020), compared to respective periods 4 years prior (2016-2019) using Poisson regression. In the three peak months of the first COVID-19 wave, there was an overall decline in hospital admissions for acute cerebrovascular diseases (RR = 0.83, 95% CI 0.78-0.89, p < 0.001), which was significant for TIA (RR = 0.61, 95% CI 0.52-0.72, p < 0.001) and ICH (0.78, 95% CI 0.67-0.91, p = 0.02), but not for IS (RR = 0.93, 95% CI 0.85-1, p = 0.08). Thrombolysis and thrombectomy numbers were not different compared to respective months 4 years prior. In the recovery period after the first COVID-19 wave, TIA (RR = 0.82, 95% CI 0.71-0.96, p = 0.011) and ICH (RR = 0.86, 95% CI 0.74-0.99, p = 0.045) hospitalizations remained lower, while the frequency of IS and recanalization treatments was unchanged. In this state-wide analysis covering all types of acute cerebrovascular diseases, hospital admissions for TIA and ICH were reduced during and also after the first wave of the COVID-19 pandemic, but hospitalizations and recanalization treatments for IS were not affected in these two periods.
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Colonna I, Koini M, Pirpamer L, Damulina A, Hofer E, Schwingenschuh P, Enzinger C, Schmidt R, Ropele S. Microstructural Tissue Changes in Alzheimer Disease Brains: Insights from Magnetization Transfer Imaging. AJNR Am J Neuroradiol 2021; 42:688-693. [PMID: 33509922 DOI: 10.3174/ajnr.a6975] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 10/23/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Reductions in magnetization transfer ratio have been associated with brain microstructural damage. We aim to compare magnetization transfer ratio in global and regional GM and WM between individuals with Alzheimer disease and healthy control participants to analyze the relationship between magnetization transfer ratio and cognitive functioning in Alzheimer disease. MATERIALS AND METHODS In this prospective study, participants with Alzheimer disease and a group of age-matched healthy control participants underwent clinical examinations and 3T MR imaging. Magnetization transfer ratios were determined in the cortex, AD-signature regions, normal-appearing WM, and WM hyperintensities. RESULTS Seventy-seven study participants (mean age ± SD, 72 ± 8 years; 47 female) and 77 age-matched healthy control participants (mean age ± SD, 72 ± 8 years; 44 female) were evaluated. Magnetization transfer ratio values were lower in patients with Alzheimer disease than in healthy control participants in all investigated regions. When adjusting for atrophy and extent of WM hyperintensities, significant differences were seen in the global cortex (OR = 0.47; 95% CI: 0.22, 0.97; P = .04), in Alzheimer disease-signature regions (OR = 0.31; 95% CI: 0.14, 0.67; P = .003), in normal-appearing WM (OR = 0.59; 95% CI: 0.39, 0.88; P = .01), and in WM hyperintensities (OR = 0.18; 95% CI: 0.09, 0.33; P ≤ .001). The magnetization transfer ratio in these regions was an independent determinant of AD. When correcting for atrophy and WM hyperintensity extent, lower GM magnetization transfer ratios were associated with poorer global cognition, language function, and constructional praxis. CONCLUSIONS Alzheimer disease is associated with magnetization transfer ratio reductions in GM and WM regions of the brain. Lower magnetization transfer ratios in the entire cortex and AD-signature regions contribute to cognitive impairment independent of brain atrophy and WM damage.
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Knol MJ, Lu D, Traylor M, Adams HHH, Romero JRJ, Smith AV, Fornage M, Hofer E, Liu J, Hostettler IC, Luciano M, Trompet S, Giese AK, Hilal S, van den Akker EB, Vojinovic D, Li S, Sigurdsson S, van der Lee SJ, Jack CR, Wilson D, Yilmaz P, Satizabal CL, Liewald DCM, van der Grond J, Chen C, Saba Y, van der Lugt A, Bastin ME, Windham BG, Cheng CY, Pirpamer L, Kantarci K, Himali JJ, Yang Q, Morris Z, Beiser AS, Tozer DJ, Vernooij MW, Amin N, Beekman M, Koh JY, Stott DJ, Houlden H, Schmidt R, Gottesman RF, MacKinnon AD, DeCarli C, Gudnason V, Deary IJ, van Duijn CM, Slagboom PE, Wong TY, Rost NS, Jukema JW, Mosley TH, Werring DJ, Schmidt H, Wardlaw JM, Ikram MA, Seshadri S, Launer LJ, Markus HS. Association of common genetic variants with brain microbleeds: A genome-wide association study. Neurology 2020; 95:e3331-e3343. [PMID: 32913026 PMCID: PMC7836652 DOI: 10.1212/wnl.0000000000010852] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 08/03/2020] [Indexed: 02/07/2023] Open
Abstract
OBJECTIVE To identify common genetic variants associated with the presence of brain microbleeds (BMBs). METHODS We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs. RESULTS BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21-1.45]; p = 2.5 × 10-10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; p = 1.0 × 10-6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB. CONCLUSIONS Genetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
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Sargurupremraj M, Suzuki H, Jian X, Sarnowski C, Evans TE, Bis JC, Eiriksdottir G, Sakaue S, Terzikhan N, Habes M, Zhao W, Armstrong NJ, Hofer E, Yanek LR, Hagenaars SP, Kumar RB, van den Akker EB, McWhirter RE, Trompet S, Mishra A, Saba Y, Satizabal CL, Beaudet G, Petit L, Tsuchida A, Zago L, Schilling S, Sigurdsson S, Gottesman RF, Lewis CE, Aggarwal NT, Lopez OL, Smith JA, Valdés Hernández MC, van der Grond J, Wright MJ, Knol MJ, Dörr M, Thomson RJ, Bordes C, Le Grand Q, Duperron MG, Smith AV, Knopman DS, Schreiner PJ, Evans DA, Rotter JI, Beiser AS, Maniega SM, Beekman M, Trollor J, Stott DJ, Vernooij MW, Wittfeld K, Niessen WJ, Soumaré A, Boerwinkle E, Sidney S, Turner ST, Davies G, Thalamuthu A, Völker U, van Buchem MA, Bryan RN, Dupuis J, Bastin ME, Ames D, Teumer A, Amouyel P, Kwok JB, Bülow R, Deary IJ, Schofield PR, Brodaty H, Jiang J, Tabara Y, Setoh K, Miyamoto S, Yoshida K, Nagata M, Kamatani Y, Matsuda F, Psaty BM, Bennett DA, De Jager PL, Mosley TH, Sachdev PS, Schmidt R, Warren HR, Evangelou E, Trégouët DA, Ikram MA, Wen W, DeCarli C, Srikanth VK, Jukema JW, Slagboom EP, Kardia SLR, Okada Y, Mazoyer B, Wardlaw JM, Nyquist PA, Mather KA, Grabe HJ, Schmidt H, Van Duijn CM, Gudnason V, Longstreth WT, Launer LJ, Lathrop M, Seshadri S, Tzourio C, Adams HH, Matthews PM, Fornage M, Debette S. Cerebral small vessel disease genomics and its implications across the lifespan. Nat Commun 2020; 11:6285. [PMID: 33293549 PMCID: PMC7722866 DOI: 10.1038/s41467-020-19111-2] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 09/10/2020] [Indexed: 12/14/2022] Open
Abstract
White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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Kneihsl M, Hofer E, Enzinger C, Niederkorn K, Horner S, Pinter D, Fandler-Höfler S, Eppinger S, Haidegger M, Schmidt R, Gattringer T. Intracranial Pulsatility in Relation to Severity and Progression of Cerebral White Matter Hyperintensities. Stroke 2020; 51:3302-3309. [DOI: 10.1161/strokeaha.120.030478] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose:
Previous studies suggested an association between increased intracranial arterial pulsatility and the severity of microangiopathic white matter hyperintensities (WMH). However, possible confounders such as age and hypertension were seldomly considered and longitudinal data are lacking. We here aimed to explore whether increased middle cerebral artery pulsatility is associated with baseline severity and progression of cerebral small vessel disease–related WMH in elderly individuals.
Methods:
The study population consisted of elderly participants from the community-based ASPS (Austrian Stroke Prevention Study). Baseline and follow-up assessment comprised transcranial Doppler sonography, brain magnetic resonance imaging, and clinical/laboratory examination of vascular risk factors. Pulsatility index on transcranial Doppler sonography was averaged from baseline indices of both middle cerebral arteries and was correlated with baseline WMH severity and WMH progression over a median follow-up period of 5 years in uni- and multivariable analyses. WMH severity was graded according to the Fazekas scale, and WMH load was quantified by semiautomated volumetric assessment.
Results:
The study cohort comprised 491 participants (mean age: 60.7±6.9 years; female: 48.5%). Pulsatility index was increased in participants with more severe WMH at baseline (
P
<0.001) but was not associated with WMH progression during follow-up (r
s
: 0.097,
P
=0.099). In multivariable analyses, only arterial hypertension remained significantly associated with baseline severity (
P
=0.04) and progression (
P
=0.008) of WMH, although transcranial Doppler sonography pulsatility index was not predictive (
P
>0.1, respectively).
Conclusions:
This community-based cohort study of elderly individuals does not support the pulsatility index of the middle cerebral artery on transcranial Doppler sonography as an independent marker of microangiopathic WMH severity and progression over time.
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Seifert-Held T, Eberhard K, Christensen S, Hofer E, Enzinger C, Albers GW, Lansberg M. Circle of Willis variants are not associated with thrombectomy outcomes. Stroke Vasc Neurol 2020; 6:310-313. [PMID: 33046661 PMCID: PMC8258040 DOI: 10.1136/svn-2020-000491] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/03/2020] [Accepted: 09/09/2020] [Indexed: 11/23/2022] Open
Abstract
Background The circle of Willis (COW) is part of the brain collateral system. The absence of COW segments may affect functional outcome in patients with ischaemic stroke undergoing endovascular therapy. Methods In 182 patients in the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution 2 Study and the CT Perfusion to Predict Response to Recanalisation in Ischaemic Stroke Project, COW anatomy was evaluated on postinterventional magnetic resonance angiography. The absence of the posterior communicating artery or the first segments of posterior or anterior cerebral arteries ipsilateral to the ischaemic infarction was rated as an incomplete COW. Logistic regression was applied to evaluate an association with the patients’ modified Rankin scale (mRS) at 90 days after stroke Results An incomplete ipsilateral COW was not predictive of the patients’ mRS at 90 days after stroke. Significant associations were shown for the patients’ baseline National Institutes of Health Stroke Scale (NIHSS), age and reperfusion status. The effect size suggests that a significant association of an incomplete COW with the mRS at 90 days may be obtained in cohorts of more than 3000 patients. Conclusions Compared with the established predictors NIHSS, age and reperfusion status, an incomplete COW is not associated with functional outcome after endovascular therapy.
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Hofer E, Roshchupkin GV, Adams HHH, Knol MJ, Lin H, Li S, Zare H, Ahmad S, Armstrong NJ, Satizabal CL, Bernard M, Bis JC, Gillespie NA, Luciano M, Mishra A, Scholz M, Teumer A, Xia R, Jian X, Mosley TH, Saba Y, Pirpamer L, Seiler S, Becker JT, Carmichael O, Rotter JI, Psaty BM, Lopez OL, Amin N, van der Lee SJ, Yang Q, Himali JJ, Maillard P, Beiser AS, DeCarli C, Karama S, Lewis L, Harris M, Bastin ME, Deary IJ, Veronica Witte A, Beyer F, Loeffler M, Mather KA, Schofield PR, Thalamuthu A, Kwok JB, Wright MJ, Ames D, Trollor J, Jiang J, Brodaty H, Wen W, Vernooij MW, Hofman A, Uitterlinden AG, Niessen WJ, Wittfeld K, Bülow R, Völker U, Pausova Z, Bruce Pike G, Maingault S, Crivello F, Tzourio C, Amouyel P, Mazoyer B, Neale MC, Franz CE, Lyons MJ, Panizzon MS, Andreassen OA, Dale AM, Logue M, Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, Lind PA, Pizzagalli F, Stein JL, Thompson PM, Medland SE, Sachdev PS, Kremen WS, Wardlaw JM, Villringer A, van Duijn CM, Grabe HJ, Longstreth WT, Fornage M, Paus T, Debette S, Ikram MA, Schmidt H, Schmidt R, Seshadri S. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults. Nat Commun 2020; 11:4796. [PMID: 32963231 PMCID: PMC7508833 DOI: 10.1038/s41467-020-18367-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 08/20/2020] [Indexed: 12/22/2022] Open
Abstract
Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging. Cortex morphology varies with age, cognitive function, and in neurological and psychiatric diseases. Here the authors report 160 genome-wide significant associations with thickness, surface area and volume of the total cortex and 34 cortical regions from a GWAS meta-analysis in 22,824 adults.
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Damulina A, Pirpamer L, Soellradl M, Sackl M, Tinauer C, Hofer E, Enzinger C, Gesierich B, Duering M, Ropele S, Schmidt R, Langkammer C. Cross-sectional and Longitudinal Assessment of Brain Iron Level in Alzheimer Disease Using 3-T MRI. Radiology 2020; 296:619-626. [PMID: 32602825 DOI: 10.1148/radiol.2020192541] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Background Deep gray matter structures in patients with Alzheimer disease (AD) contain higher brain iron concentrations. However, few studies have included neocortical areas, which are challenging to assess with MRI. Purpose To investigate baseline and change in brain iron levels using MRI at 3 T with R2* relaxation rate mapping in individuals with AD compared with healthy control (HC) participants. Materials and Methods In this prospective study, participants with AD recruited between 2010 and 2016 and age-matched HC participants selected from 2010 to 2014 were evaluated. Of 100 participants with AD, 56 underwent subsequent neuropsychological testing and brain MRI at a mean follow-up of 17 months. All participants underwent 3-T MRI, including R2* mapping corrected for macroscopic B0 field inhomogeneities. Anatomic structures were segmented, and median R2* values were calculated in the neocortex and cortical lobes, basal ganglia (BG), hippocampi, and thalami. Multivariable linear regression analysis was applied to study the difference in R2* levels between groups and the association between longitudinal changes in R2* values and cognition in the AD group. Results A total of 100 participants with AD (mean age, 73 years ± 9 [standard deviation]; 58 women) and 100 age-matched HC participants (mean age, 73 years ± 9; 60 women) were evaluated. Median R2* levels were higher in the AD group than in the HC group in the BG (HC, 29.0 sec-1; AD, 30.2 sec-1; P = .01) and total neocortex (HC, 17.0 sec-1; AD, 17.4 sec-1; P < .001) and regionally in the occipital (HC, 19.6 sec-1; AD, 20.2 sec-1; P = .007) and temporal (HC, 16.4 sec-1; AD, 18.1 sec-1; P < .001) lobes. R2* values in the temporal lobe were associated with longitudinal changes in Consortium to Establish a Registry for Alzheimer's Disease total score (β = -3.23 score/sec-1, P = .003) in participants with AD independent of longitudinal changes in brain volume. Conclusion Iron concentration in the deep gray matter and neocortical regions was higher in patients with Alzheimer disease than in healthy control participants. Change in iron levels over time in the temporal lobe was associated with cognitive decline in individuals with Alzheimer disease. © RSNA, 2020 Online supplemental material is available for this article.
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Rabensteiner J, Hofer E, Fauler G, Fritz-Petrin E, Benke T, Dal-Bianco P, Ransmayr G, Schmidt R, Herrmann M. The impact of folate and vitamin B12 status on cognitive function and brain atrophy in healthy elderly and demented Austrians, a retrospective cohort study. Aging (Albany NY) 2020; 12:15478-15491. [PMID: 32706338 PMCID: PMC7467363 DOI: 10.18632/aging.103714] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 07/06/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Dementia, and in particular Alzheimer's disease (AD), is a debilitating progressive disease with high prevalence in our society. Vitamin B12 and folate deficiency are potential modifiable risk factors. However, previous studies reported inconsistent results. RESULTS The average concentrations of all biochemical markers were within the respective reference ranges. Cross-sectional and longitudinal analyses did not reveal significant associations between biochemical markers and cognitive function, global or regional brain volume, cortical thickness or cortical surface area, neither in controls nor in AD patients. CONCLUSIONS Variations of direct and indirect markers of B12 and folate status are not associated with cognitive dysfunction and brain atrophy. METHODS This retrospective study explored the association between biochemical markers of B12 and folate status, cognitive function and MRI-based brain atrophy in cognitive normal elderly (controls) and AD patients. Folate, total and active vitamin B12 and MMA were measured in blood samples from 378 controls and 217 AD patients. Neuropsychiatric tests capturing memory, executive function and visuopractical skills were performed in all participants. Brain atrophy was assessed by MRI in 155 controls and 217 AD patients. In a subset of participants cognitive testing (n=234) and MRI (n=182) was repeated after an average median between 1.25 and 6.25 years.
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Armstrong NJ, Mather KA, Sargurupremraj M, Knol MJ, Malik R, Satizabal CL, Yanek LR, Wen W, Gudnason VG, Dueker ND, Elliott LT, Hofer E, Bis J, Jahanshad N, Li S, Logue MA, Luciano M, Scholz M, Smith AV, Trompet S, Vojinovic D, Xia R, Alfaro-Almagro F, Ames D, Amin N, Amouyel P, Beiser AS, Brodaty H, Deary IJ, Fennema-Notestine C, Gampawar PG, Gottesman R, Griffanti L, Jack CR, Jenkinson M, Jiang J, Kral BG, Kwok JB, Lampe L, C M Liewald D, Maillard P, Marchini J, Bastin ME, Mazoyer B, Pirpamer L, Rafael Romero J, Roshchupkin GV, Schofield PR, Schroeter ML, Stott DJ, Thalamuthu A, Trollor J, Tzourio C, van der Grond J, Vernooij MW, Witte VA, Wright MJ, Yang Q, Morris Z, Siggurdsson S, Psaty B, Villringer A, Schmidt H, Haberg AK, van Duijn CM, Jukema JW, Dichgans M, Sacco RL, Wright CB, Kremen WS, Becker LC, Thompson PM, Mosley TH, Wardlaw JM, Ikram MA, Adams HHH, Seshadri S, Sachdev PS, Smith SM, Launer L, Longstreth W, DeCarli C, Schmidt R, Fornage M, Debette S, Nyquist PA. Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities. Stroke 2020; 51:2111-2121. [PMID: 32517579 DOI: 10.1161/strokeaha.119.027544] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
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Katschnig-Winter P, Enzinger C, Bohlsen D, Magyar M, Seiler S, Hofer E, Franthal S, Homayoon N, Kögl M, Wenzel K, Deutschmann H, Fazekas F, Schmidt R, Schwingenschuh P. Minor Structural Differences in the Cervical Spine Between Patients With Cervical Dystonia and Age-Matched Healthy Controls. Front Neurol 2020; 11:472. [PMID: 32547481 PMCID: PMC7272577 DOI: 10.3389/fneur.2020.00472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/29/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Cervical dystonia is the most common form of focal dystonia. The frequency and pattern of degenerative changes of the cervical spine in patients with cervical dystonia and their relation to clinical symptoms remain unclear as no direct comparison to healthy controls has been performed yet. Here, we used magnetic resonance imaging (MRI) to investigate (1) whether structural abnormalities of the cervical spine are more common in patients with cervical dystonia compared to age-matched healthy controls, (2) if there are clinical predictors for abnormalities on MRI, and (3) to calculate the inter-rater reliability of the respective radiological scales. Methods: Twenty-five consecutive patients with cervical dystonia and 20 age-matched healthy controls were included in the study. MRI scans of the cervical spine were analyzed separately by three experienced raters blinded to clinical information, applying different MRI rating scales. Structural abnormalities were compared between groups for upper, middle, and lower cervical spine segments. The associations between scores differentiating both groups and clinical parameters were assessed in dystonia patients. Additionally, inter-rater reliability of the MRI scales was calculated. Results: Comparing structural abnormalities, we found minor differences in the middle cervical spine, indicated by a higher MRI total score in patients but no significant correlation between clinical parameters and MRI changes. Inter-rater reliability was satisfying for most of the MRI rating scales. Conclusion: Our results do not provide evidence for a role of MRI of the cervical spine in the routine work-up of patients with cervical dystonia in the absence of specific clinical signs or symptoms.
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Shin J, Ma S, Hofer E, Patel Y, Vosberg DE, Tilley S, Roshchupkin GV, Sousa AMM, Jian X, Gottesman R, Mosley TH, Fornage M, Saba Y, Pirpamer L, Schmidt R, Schmidt H, Carrion-Castillo A, Crivello F, Mazoyer B, Bis JC, Li S, Yang Q, Luciano M, Karama S, Lewis L, Bastin ME, Harris MA, Wardlaw JM, Deary IE, Scholz M, Loeffler M, Witte AV, Beyer F, Villringer A, Armstrong NJ, Mather KA, Ames D, Jiang J, Kwok JB, Schofield PR, Thalamuthu A, Trollor JN, Wright MJ, Brodaty H, Wen W, Sachdev PS, Terzikhan N, Evans TE, Adams HHHH, Ikram MA, Frenzel S, Auwera-Palitschka SVD, Wittfeld K, Bülow R, Grabe HJ, Tzourio C, Mishra A, Maingault S, Debette S, Gillespie NA, Franz CE, Kremen WS, Ding L, Jahanshad N, Sestan N, Pausova Z, Seshadri S, Paus T. Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes. Cereb Cortex 2020; 30:4121-4139. [PMID: 32198502 DOI: 10.1093/cercor/bhaa035] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation.
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Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, Lind PA, Pizzagalli F, Ching CRK, McMahon MAB, Shatokhina N, Zsembik LCP, Thomopoulos SI, Zhu AH, Strike LT, Agartz I, Alhusaini S, Almeida MAA, Alnæs D, Amlien IK, Andersson M, Ard T, Armstrong NJ, Ashley-Koch A, Atkins JR, Bernard M, Brouwer RM, Buimer EEL, Bülow R, Bürger C, Cannon DM, Chakravarty M, Chen Q, Cheung JW, Couvy-Duchesne B, Dale AM, Dalvie S, de Araujo TK, de Zubicaray GI, de Zwarte SMC, den Braber A, Doan NT, Dohm K, Ehrlich S, Engelbrecht HR, Erk S, Fan CC, Fedko IO, Foley SF, Ford JM, Fukunaga M, Garrett ME, Ge T, Giddaluru S, Goldman AL, Green MJ, Groenewold NA, Grotegerd D, Gurholt TP, Gutman BA, Hansell NK, Harris MA, Harrison MB, Haswell CC, Hauser M, Herms S, Heslenfeld DJ, Ho NF, Hoehn D, Hoffmann P, Holleran L, Hoogman M, Hottenga JJ, Ikeda M, Janowitz D, Jansen IE, Jia T, Jockwitz C, Kanai R, Karama S, Kasperaviciute D, Kaufmann T, Kelly S, Kikuchi M, Klein M, Knapp M, Knodt AR, Krämer B, Lam M, Lancaster TM, Lee PH, Lett TA, Lewis LB, Lopes-Cendes I, Luciano M, Macciardi F, Marquand AF, Mathias SR, Melzer TR, Milaneschi Y, Mirza-Schreiber N, Moreira JCV, Mühleisen TW, Müller-Myhsok B, Najt P, Nakahara S, Nho K, Loohuis LMO, Orfanos DP, Pearson JF, Pitcher TL, Pütz B, Quidé Y, Ragothaman A, Rashid FM, Reay WR, Redlich R, Reinbold CS, Repple J, Richard G, Riede BC, Risacher SL, Rocha CS, Mota NR, Salminen L, Saremi A, Saykin AJ, Schlag F, Schmaal L, Schofield PR, Secolin R, Shapland CY, Shen L, Shin J, Shumskaya E, Sønderby IE, Sprooten E, Tansey KE, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Turner JA, Uhlmann A, Vallerga CL, van derMeer D, van Donkelaar MMJ, van Eijk L, van Erp TGM, van Haren NEM, van Rooij D, van Tol MJ, Veldink JH, Verhoef E, Walton E, Wang M, Wang Y, Wardlaw JM, Wen W, Westlye LT, Whelan CD, Witt SH, Wittfeld K, Wolf C, Wolfers T, Wu JQ, Yasuda CL, Zaremba D, Zhang Z, Zwiers MP, Artiges E, Assareh AA, Ayesa-Arriola R, Belger A, Brandt CL, Brown GG, Cichon S, Curran JE, Davies GE, Degenhardt F, Dennis MF, Dietsche B, Djurovic S, Doherty CP, Espiritu R, Garijo D, Gil Y, Gowland PA, Green RC, Häusler AN, Heindel W, Ho BC, Hoffmann WU, Holsboer F, Homuth G, Hosten N, Jack CR, Jang M, Jansen A, Kimbrel NA, Kolskår K, Koops S, Krug A, Lim KO, Luykx JJ, Mathalon DH, Mather KA, Mattay VS, Matthews S, Van Son JM, McEwen SC, Melle I, Morris DW, Mueller BA, Nauck M, Nordvik JE, Nöthen MM, O’Leary DS, Opel N, Martinot MLP, Pike GB, Preda A, Quinlan EB, Rasser PE, Ratnakar V, Reppermund S, Steen VM, Tooney PA, Torres FR, Veltman DJ, Voyvodic JT, Whelan R, White T, Yamamori H, Adams HHH, Bis JC, Debette S, Decarli C, Fornage M, Gudnason V, Hofer E, Ikram MA, Launer L, Longstreth WT, Lopez OL, Mazoyer B, Mosley TH, Roshchupkin GV, Satizabal CL, Schmidt R, Seshadri S, Yang Q, Alvim MKM, Ames D, Anderson TJ, Andreassen OA, Arias-Vasquez A, Bastin ME, Baune BT, Beckham JC, Blangero J, Boomsma DI, Brodaty H, Brunner HG, Buckner RL, Buitelaar JK, Bustillo JR, Cahn W, Cairns MJ, Calhoun V, Carr VJ, Caseras X, Caspers S, Cavalleri GL, Cendes F, Corvin A, Crespo-Facorro B, Dalrymple-Alford JC, Dannlowski U, de Geus EJC, Deary IJ, Delanty N, Depondt C, Desrivières S, Donohoe G, Espeseth T, Fernández G, Fisher SE, Flor H, Forstner AJ, Francks C, Franke B, Glahn DC, Gollub RL, Grabe HJ, Gruber O, Håberg AK, Hariri AR, Hartman CA, Hashimoto R, Heinz A, Henskens FA, Hillegers MHJ, Hoekstra PJ, Holmes AJ, Hong LE, Hopkins WD, Pol HEH, Jernigan TL, Jönsson EG, Kahn RS, Kennedy MA, Kircher TTJ, Kochunov P, Kwok JBJ, Le Hellard S, Loughland CM, Martin NG, Martinot JL, McDonald C, McMahon KL, Meyer-Lindenberg A, Michie PT, Morey RA, Mowry B, Nyberg L, Oosterlaan J, Ophoff RA, Pantelis C, Paus T, Pausova Z, Penninx BWJH, Polderman TJC, Posthuma D, Rietschel M, Roffman JL, Rowland LM, Sachdev PS, Sämann PG, Schall U, Schumann G, Scott RJ, Sim K, Sisodiya SM, Smoller JW, Sommer IE, St Pourcain B, Stein DJ, Toga AW, Trollor JN, Van der Wee NJA, van ‘t Ent D, Völzke H, Walter H, Weber B, Weinberger DR, Wright MJ, Zhou J, Stein JL, Thompson PM, Medland SE. The genetic architecture of the human cerebral cortex. Science 2020; 367:eaay6690. [PMID: 32193296 PMCID: PMC7295264 DOI: 10.1126/science.aay6690] [Citation(s) in RCA: 372] [Impact Index Per Article: 93.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 02/10/2020] [Indexed: 12/15/2022]
Abstract
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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Amin Al Olama A, Wason JMS, Tuladhar AM, van Leijsen EMC, Koini M, Hofer E, Morris RG, Schmidt R, de Leeuw FE, Markus HS. Simple MRI score aids prediction of dementia in cerebral small vessel disease. Neurology 2020; 94:e1294-e1302. [PMID: 32123050 PMCID: PMC7274929 DOI: 10.1212/wnl.0000000000009141] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 10/01/2019] [Indexed: 12/22/2022] Open
Abstract
Objective To determine whether a simple small vessel disease (SVD) score, which uses information available on rapid visual assessment of clinical MRI scans, predicts risk of cognitive decline and dementia, above that provided by simple clinical measures. Methods Three prospective longitudinal cohort studies (SCANS [St George's Cognition and Neuroimaging in Stroke], RUN DMC [Radboud University Nijmegen Diffusion Imaging and Magnetic Resonance Imaging Cohort], and the ASPS [Austrian Stroke Prevention Study]), which covered a range of SVD severity from mild and asymptomatic to severe and symptomatic, were included. In all studies, MRI was performed at baseline, cognitive tests repeated during follow-up, and progression to dementia recorded prospectively. Outcome measures were cognitive decline and onset of dementia during follow-up. We determined whether the SVD score predicted risk of cognitive decline and future dementia. We also determined whether using the score to select a group of patients with more severe disease would reduce sample sizes for clinical intervention trials. Results In a pooled analysis of all 3 cohorts, the score improved prediction of dementia (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.81–0.89) compared with that from clinical risk factors alone (AUC, 0.76; 95% CI, 0.71–0.81). Predictive performance was higher in patients with more severe SVD. Power calculations showed selecting patients with a higher score reduced sample sizes required for hypothetical clinical trials by 40%–66% depending on the outcome measure used. Conclusions A simple SVD score, easily obtainable from clinical MRI scans and therefore applicable in routine clinical practice, aided prediction of future dementia risk.
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Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, Scholz M, Sargurupremraj M, Jahanshad N, Roshchupkin GV, Smith AV, Bis JC, Jian X, Luciano M, Hofer E, Teumer A, van der Lee SJ, Yang J, Yanek LR, Lee TV, Li S, Hu Y, Koh JY, Eicher JD, Desrivières S, Arias-Vasquez A, Chauhan G, Athanasiu L, Rentería ME, Kim S, Hoehn D, Armstrong NJ, Chen Q, Holmes AJ, den Braber A, Kloszewska I, Andersson M, Espeseth T, Grimm O, Abramovic L, Alhusaini S, Milaneschi Y, Papmeyer M, Axelsson T, Ehrlich S, Roiz-Santiañez R, Kraemer B, Håberg AK, Jones HJ, Pike GB, Stein DJ, Stevens A, Bralten J, Vernooij MW, Harris TB, Filippi I, Witte AV, Guadalupe T, Wittfeld K, Mosley TH, Becker JT, Doan NT, Hagenaars SP, Saba Y, Cuellar-Partida G, Amin N, Hilal S, Nho K, Mirza-Schreiber N, Arfanakis K, Becker DM, Ames D, Goldman AL, Lee PH, Boomsma DI, Lovestone S, Giddaluru S, Le Hellard S, Mattheisen M, Bohlken MM, Kasperaviciute D, Schmaal L, Lawrie SM, Agartz I, Walton E, Tordesillas-Gutierrez D, Davies GE, Shin J, Ipser JC, Vinke LN, Hoogman M, Jia T, Burkhardt R, Klein M, Crivello F, Janowitz D, Carmichael O, Haukvik UK, Aribisala BS, Schmidt H, Strike LT, Cheng CY, Risacher SL, Pütz B, Fleischman DA, Assareh AA, Mattay VS, Buckner RL, Mecocci P, Dale AM, Cichon S, Boks MP, Matarin M, Penninx BWJH, Calhoun VD, Chakravarty MM, Marquand AF, Macare C, Kharabian Masouleh S, Oosterlaan J, Amouyel P, Hegenscheid K, Rotter JI, Schork AJ, Liewald DCM, de Zubicaray GI, Wong TY, Shen L, Sämann PG, Brodaty H, Roffman JL, de Geus EJC, Tsolaki M, Erk S, van Eijk KR, Cavalleri GL, van der Wee NJA, McIntosh AM, Gollub RL, Bulayeva KB, Bernard M, Richards JS, Himali JJ, Loeffler M, Rommelse N, Hoffmann W, Westlye LT, Valdés Hernández MC, Hansell NK, van Erp TGM, Wolf C, Kwok JBJ, Vellas B, Heinz A, Olde Loohuis LM, Delanty N, Ho BC, Ching CRK, Shumskaya E, Singh B, Hofman A, van der Meer D, Homuth G, Psaty BM, Bastin ME, Montgomery GW, Foroud TM, Reppermund S, Hottenga JJ, Simmons A, Meyer-Lindenberg A, Cahn W, Whelan CD, van Donkelaar MMJ, Yang Q, Hosten N, Green RC, Thalamuthu A, Mohnke S, Hulshoff Pol HE, Lin H, Jack CR, Schofield PR, Mühleisen TW, Maillard P, Potkin SG, Wen W, Fletcher E, Toga AW, Gruber O, Huentelman M, Davey Smith G, Launer LJ, Nyberg L, Jönsson EG, Crespo-Facorro B, Koen N, Greve DN, Uitterlinden AG, Weinberger DR, Steen VM, Fedko IO, Groenewold NA, Niessen WJ, Toro R, Tzourio C, Longstreth WT, Ikram MK, Smoller JW, van Tol MJ, Sussmann JE, Paus T, Lemaître H, Schroeter ML, Mazoyer B, Andreassen OA, Holsboer F, Depondt C, Veltman DJ, Turner JA, Pausova Z, Schumann G, van Rooij D, Djurovic S, Deary IJ, McMahon KL, Müller-Myhsok B, Brouwer RM, Soininen H, Pandolfo M, Wassink TH, Cheung JW, Wolfers T, Martinot JL, Zwiers MP, Nauck M, Melle I, Martin NG, Kanai R, Westman E, Kahn RS, Sisodiya SM, White T, Saremi A, van Bokhoven H, Brunner HG, Völzke H, Wright MJ, van 't Ent D, Nöthen MM, Ophoff RA, Buitelaar JK, Fernández G, Sachdev PS, Rietschel M, van Haren NEM, Fisher SE, Beiser AS, Francks C, Saykin AJ, Mather KA, Romanczuk-Seiferth N, Hartman CA, DeStefano AL, Heslenfeld DJ, Weiner MW, Walter H, Hoekstra PJ, Nyquist PA, Franke B, Bennett DA, Grabe HJ, Johnson AD, Chen C, van Duijn CM, Lopez OL, Fornage M, Wardlaw JM, Schmidt R, DeCarli C, De Jager PL, Villringer A, Debette S, Gudnason V, Medland SE, Shulman JM, Thompson PM, Seshadri S, Ikram MA. Genetic architecture of subcortical brain structures in 38,851 individuals. Nat Genet 2019; 51:1624-1636. [PMID: 31636452 PMCID: PMC7055269 DOI: 10.1038/s41588-019-0511-y] [Citation(s) in RCA: 156] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 09/05/2019] [Indexed: 12/15/2022]
Abstract
Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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