Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 31 entries
Sorted by: Best Match Show Resources per page
Apolipoprotein E levels in cerebrospinal fluid and the effects of ABCA1 polymorphisms.

Molecular neurodegeneration

Wahrle SE, Shah AR, Fagan AM, Smemo S, Kauwe JS, Grupe A, Hinrichs A, Mayo K, Jiang H, Thal LJ, Goate AM, Holtzman DM.
PMID: 17430597
Mol Neurodegener. 2007 Apr 12;2:7. doi: 10.1186/1750-1326-2-7.

BACKGROUND: Animal studies suggest that brain apolipoprotein E (apoE) levels influence amyloid-beta (Abeta) deposition and thus risk for Alzheimer's disease (AD). We have previously demonstrated that deletion of the ATP-binding cassette A1 transporter (ABCA1) in mice causes dramatic reductions...

Not Just Par for the Course: 73 Quaternary Germanides RE.

Inorganic chemistry

Zhang D, Oliynyk AO, Duarte GM, Iyer AK, Ghadbeigi L, Kauwe SK, Sparks TD, Mar A.
PMID: 30365327
Inorg Chem. 2018 Nov 19;57(22):14249-14259. doi: 10.1021/acs.inorgchem.8b02279. Epub 2018 Oct 26.

A total of 73 new quaternary rare-earth germanides RE

Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications.

Inorganic chemistry

Belviso F, Claerbout VEP, Comas-Vives A, Dalal NS, Fan FR, Filippetti A, Fiorentini V, Foppa L, Franchini C, Geisler B, Ghiringhelli LM, Groß A, Hu S, Íñiguez J, Kauwe SK, Musfeldt JL, Nicolini P, Pentcheva R, Polcar T, Ren W, Ricci F, Ricci F, Sen HS, Skelton JM, Sparks TD, Stroppa A, Urru A, Vandichel M, Vavassori P, Wu H, Yang K, Zhao HJ, Puggioni D, Cortese R, Cammarata A.
PMID: 31668070
Inorg Chem. 2019 Nov 18;58(22):14939-14980. doi: 10.1021/acs.inorgchem.9b01785. Epub 2019 Oct 31.

Nanostructured materials are essential building blocks for the fabrication of new devices for energy harvesting/storage, sensing, catalysis, magnetic, and optoelectronic applications. However, because of the increase of technological needs, it is essential to identify new functional materials and improve...

Benchmark datasets incorporating diverse tasks, sample sizes, material systems, and data heterogeneity for materials informatics.

Data in brief

Henderson AN, Kauwe SK, Sparks TD.
PMID: 34345637
Data Brief. 2021 Jul 13;37:107262. doi: 10.1016/j.dib.2021.107262. eCollection 2021 Aug.

Materials discovery via machine learning has become an increasingly popular method due to its ability to rapidly predict materials properties in a time-efficient and low-cost manner. However, one limitation in this field is the lack of benchmark datasets, particularly...

Association between WWOX/MAF variants and dementia-related neuropathologic endophenotypes.

Neurobiology of aging

Dugan AJ, Nelson PT, Katsumata Y, Shade LMP, Teylan MA, Boehme KL, Mukherjee S, Kauwe JSK, Hohman TJ, Schneider JA, Fardo DW.
PMID: 34852950
Neurobiol Aging. 2022 Mar;111:95-106. doi: 10.1016/j.neurobiolaging.2021.10.011. Epub 2021 Oct 29.

The genetic locus containing the WWOX and MAF genes was implicated as a clinical Alzheimer's disease (AD) risk locus in two recent large meta-analytic genome wide association studies (GWAS). In a prior GWAS, we identified a variant in WWOX...

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association

Teerlink CC, Miller JB, Vance EL, Staley LA, Stevens J, Tavana JP, Cloward ME, Page ML, Dayton L, Cannon-Albright LA, Kauwe JSK.
PMID: 34151536
Alzheimers Dement. 2021 Jun 20; doi: 10.1002/alz.12397. Epub 2021 Jun 20.

INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were...

Author Correction: Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

Nature genetics

Kunkle BW, Grenier-Boley B, Sims R, Bis JC, Damotte V, Naj AC, Boland A, Vronskaya M, van der Lee SJ, Amlie-Wolf A, Bellenguez C, Frizatti A, Chouraki V, Martin ER, Sleegers K, Badarinarayan N, Jakobsdottir J, Hamilton-Nelson KL, Moreno-Grau S, Olaso R, Raybould R, Chen Y, Kuzma AB, Hiltunen M, Morgan T, Ahmad S, Vardarajan BN, Epelbaum J, Hoffmann P, Boada M, Beecham GW, Garnier JG, Harold D, Fitzpatrick AL, Valladares O, Moutet ML, Gerrish A, Smith AV, Qu L, Bacq D, Denning N, Jian X, Zhao Y, Del Zompo M, Fox NC, Choi SH, Mateo I, Hughes JT, Adams HH, Malamon J, Sanchez-Garcia F, Patel Y, Brody JA, Dombroski BA, Naranjo MCD, Daniilidou M, Eiriksdottir G, Mukherjee S, Wallon D, Uphill J, Aspelund T, Cantwell LB, Garzia F, Galimberti D, Hofer E, Butkiewicz M, Fin B, Scarpini E, Sarnowski C, Bush WS, Meslage S, Kornhuber J, White CC, Song Y, Barber RC, Engelborghs S, Sordon S, Voijnovic D, Adams PM, Vandenberghe R, Mayhaus M, Cupples LA, Albert MS, De Deyn PP, Gu W, Himali JJ, Beekly D, Squassina A, Hartmann AM, Orellana A, Blacker D, Rodriguez-Rodriguez E, Lovestone S, Garcia ME, Doody RS, Munoz-Fernadez C, Sussams R, Lin H, Fairchild TJ, Benito YA, Holmes C, Karamujić-Čomić H, Frosch MP, Thonberg H, Maier W, Roshchupkin G, Ghetti B, Giedraitis V, Kawalia A, Li S, Huebinger RM, Kilander L, Moebus S, Hernández I, Kamboh MI, Brundin R, Turton J, Yang Q, Katz MJ, Concari L, Lord J, Beiser AS, Keene CD, Helisalmi S, Kloszewska I, Kukull WA, Koivisto AM, Lynch A, Tarraga L, Larson EB, Haapasalo A, Lawlor B, Mosley TH, Lipton RB, Solfrizzi V, Gill M, Longstreth WT, Montine TJ, Frisardi V, Diez-Fairen M, Rivadeneira F, Petersen RC, Deramecourt V, Alvarez I, Salani F, Ciaramella A, Boerwinkle E, Reiman EM, Fievet N, Rotter JI, Reisch JS, Hanon O, Cupidi C, Uitterlinden AGA, Royall DR, Dufouil C, Maletta RG, de Rojas I, Sano M, Brice A, Cecchetti R, George-Hyslop PS, Ritchie K, Tsolaki M, Tsuang DW, Dubois B, Craig D, Wu CK, Soininen H, Avramidou D, Albin RL, Fratiglioni L, Germanou A, Apostolova LG, Keller L, Koutroumani M, Arnold SE, Panza F, Gkatzima O, Asthana S, Hannequin D, Whitehead P, Atwood CS, Caffarra P, Hampel H, Quintela I, Carracedo Á, Lannfelt L, Rubinsztein DC, Barnes LL, Pasquier F, Frölich L, Barral S, McGuinness B, Beach TG, Johnston JA, Becker JT, Passmore P, Bigio EH, Schott JM, Bird TD, Warren JD, Boeve BF, Lupton MK, Bowen JD, Proitsi P, Boxer A, Powell JF, Burke JR, Kauwe JSK, Burns JM, Mancuso M, Buxbaum JD, Bonuccelli U, Cairns NJ, McQuillin A, Cao C, Livingston G, Carlson CS, Bass NJ, Carlsson CM, Hardy J, Carney RM, Bras J, Carrasquillo MM, Guerreiro R, Allen M, Chui HC, Fisher E, Masullo C, Crocco EA, DeCarli C, Bisceglio G, Dick M, Ma L, Duara R, Graff-Radford NR, Evans DA, Hodges A, Faber KM, Scherer M, Fallon KB, Riemenschneider M, Fardo DW, Heun R, Farlow MR, Kölsch H, Ferris S, Leber M, Foroud TM, Heuser I, Galasko DR, Giegling I, Gearing M, Hüll M, Geschwind DH, Gilbert JR, Morris J, Green RC, Mayo K, Growdon JH, Feulner T, Hamilton RL, Harrell LE, Drichel D, Honig LS, Cushion TD, Huentelman MJ, Hollingworth P, Hulette CM, Hyman BT, Marshall R, Jarvik GP, Meggy A, Abner E, Menzies GE, Jin LW, Leonenko G, Real LM, Jun GR, Baldwin CT, Grozeva D, Karydas A, Russo G, Kaye JA, Kim R, Jessen F, Kowall NW, Vellas B, Kramer JH, Vardy E, LaFerla FM, Jöckel KH, Lah JJ, Dichgans M, Leverenz JB, Mann D, Levey AI, Pickering-Brown S, Lieberman AP, Klopp N, Lunetta KL, Wichmann HE, Lyketsos CG, Morgan K, Marson DC, Brown K, Martiniuk F, Medway C, Mash DC, Nöthen MM, Masliah E, Hooper NM, McCormick WC, Daniele A, McCurry SM, Bayer A, McDavid AN, Gallacher J, McKee AC, van den Bussche H, Mesulam M, Brayne C, Miller BL, Riedel-Heller S, Miller CA, Miller JW, Al-Chalabi A, Morris JC, Shaw CE, Myers AJ, Wiltfang J, O'Bryant S, Olichney JM, Alvarez V, Parisi JE, Singleton AB, Paulson HL, Collinge J, Perry WR, Mead S, Peskind E, Cribbs DH, Rossor M, Pierce A, Ryan NS, Poon WW, Nacmias B, Potter H, Sorbi S, Quinn JF, Sacchinelli E, Raj A, Spalletta G, Raskind M, Caltagirone C, Bossù P, Orfei MD, Reisberg B, Clarke R, Reitz C, Smith AD, Ringman JM, Warden D, Roberson ED, Wilcock G, Rogaeva E, Bruni AC, Rosen HJ, Gallo M, Rosenberg RN, Ben-Shlomo Y, Sager MA, Mecocci P, Saykin AJ, Pastor P, Cuccaro ML, Vance JM, Schneider JA, Schneider LS, Slifer S, Seeley WW, Smith AG, Sonnen JA, Spina S, Stern RA, Swerdlow RH, Tang M, Tanzi RE, Trojanowski JQ, Troncoso JC, Van Deerlin VM, Van Eldik LJ, Vinters HV, Vonsattel JP, Weintraub S, Welsh-Bohmer KA, Wilhelmsen KC, Williamson J, Wingo TS, Woltjer RL, Wright CB, Yu CE, Yu L, Saba Y, Pilotto A, Bullido MJ, Peters O, Crane PK, Bennett D, Bosco P, Coto E, Boccardi V, De Jager PL, Lleo A, Warner N, Lopez OL, Ingelsson M, Deloukas P, Cruchaga C, Graff C, Gwilliam R, Fornage M, Goate AM, Sanchez-Juan P, Kehoe PG, Amin N, Ertekin-Taner N, Berr C, Debette S, Love S, Launer LJ, Younkin SG, Dartigues JF, Corcoran C, Ikram MA, Dickson DW, Nicolas G, Campion D, Tschanz J, Schmidt H, Hakonarson H, Clarimon J, Munger R, Schmidt R, Farrer LA, Van Broeckhoven C, O'Donovan MC, DeStefano AL, Jones L, Haines JL, Deleuze JF, Owen MJ, Gudnason V, Mayeux R, Escott-Price V, Psaty BM, Ramirez A, Wang LS, Ruiz A, van Duijn CM, Holmans PA, Seshadri S, Williams J, Amouyel P, Schellenberg GD, Lambert JC, Pericak-Vance MA.
PMID: 31417202
Nat Genet. 2019 Sep;51(9):1423-1424. doi: 10.1038/s41588-019-0495-7.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Pairwise Correlation Analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset Reveals Significant Feature Correlation.

Genes

Huckvale ED, Hodgman MW, Greenwood BB, Stucki DO, Ward KM, Ebbert MTW, Kauwe JSK, The Alzheimer's Disease Neuroimaging Initiative, The Alzheimer's Disease Metabolomics Consortium, Miller JB.
PMID: 34828267
Genes (Basel). 2021 Oct 21;12(11). doi: 10.3390/genes12111661.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer's disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset...

Common DNA Variants Accurately Rank an Individual of Extreme Height.

International journal of genomics

Sexton CE, Ebbert MTW, Miller RH, Ferrel M, Tschanz JAT, Corcoran CD, Ridge PG, Kauwe JSK.
PMID: 30255029
Int J Genomics. 2018 Sep 04;2018:5121540. doi: 10.1155/2018/5121540. eCollection 2018.

Polygenic scores (or genetic risk scores) quantify the aggregate of small effects from many common genetic loci that have been associated with a trait through genome-wide association. Polygenic scores were first used successfully in schizophrenia and have since been...

Erratum to: "Sex Differences in Risk for Alzheimer's Disease Related to Neurotrophin Gene Polymorphisms: The Cache County Memory Study".

The journals of gerontology. Series A, Biological sciences and medical sciences

Matyi J, Tschanz JT, Rattinger GB, Sanders C, Vernon EK, Corcoran C, Kauwe JSK, Buhusi M.
PMID: 29272340
J Gerontol A Biol Sci Med Sci. 2018 Mar 02;73(3):311. doi: 10.1093/gerona/glx220.

No abstract available.

Population genealogy resource shows evidence of familial clustering for Alzheimer disease.

Neurology. Genetics

Cannon-Albright LA, Dintelman S, Maness T, Cerny J, Thomas A, Backus S, Farnham JM, Teerlink CC, Contreras J, Kauwe JSK, Meyer LJ.
PMID: 30109265
Neurol Genet. 2018 Aug 01;4(4):e249. doi: 10.1212/NXG.0000000000000249. eCollection 2018 Aug.

OBJECTIVE: To show the potential of a resource consisting of a genealogy of the US record linked to National Veterans Health Administration (VHA) patient data for investigation of the genetic contribution to health-related phenotypes, we present an analysis of...

Genetic discoveries in AD using CSF amyloid and tau.

Current genetic medicine reports

Cruchaga C, Ebbert MT, Kauwe JS.
PMID: 24729949
Curr Genet Med Rep. 2014 Mar 01;2(1):23-29. doi: 10.1007/s40142-014-0031-0.

The use of cerebrospinal fluid levels of Aβ42 and pTau181 as endophenotypes for genetic studies of Alzheimer's disease (AD) has led to successful identification of both rare and common AD risk variants. In addition, this approach has provided meaningful...

Showing 1 to 12 of 31 entries