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37 citation(s) found for "Unit, Dominantly Inherited Alzheimer Network–Trials".

Robust, flexible, and scalable tests for Hardy–Weinberg equilibrium across diverse ancestries
Kwong, Alan , Blackwell, Thomas W. , LeFaive, Jonathon , Barnes, Kathleen C. , Boerwinkle, Eric , Cade, Brian E. , Chen, Han , Conomos, Matthew P. , Eng, Celeste , Gao, Yan , Irvin, Marguerite R. , Kelly, Tanika N. , Kim, Wonji , Lubitz, Steven A. , Mathias, Rasika A. , Montasser, May E. , Musani, Solomon K., Palmer, Nicholette D, Qiao, Dandi , Reiner, Alex P. , Roden, Dan M. , Shoemaker, M. Benjamin , Smith, Jennifer A. , Smith, Nicholas L. , Lasky‐Su, Jessica , Tiwari, Hemant K., Weeks, Daniel E. , Group, TOPMed Analysis Working, Scott, Laura J. , Smith, Albert V. , Boehnke, Michael , Kang, Hyun Min , Palmer, Nicholette D. , Smith, Jennifer A , Lubitz, Steven A , Smith, Albert V , Kelly, Tanika N , Weeks, Daniel E , Palmer, Nicholette D , Mathias, Rasika A , Cade, Brian E , Lasky-Su, Jessica , Andrade, Mariza de , Barnard, John , Blangero, John , Burchard, Esteban G. , Chasman, Daniel I. , Cupples, L. Adrienne , Ellinor, Patrick T. , Guo, Xiuqing , Kooperberg, Charles , Mak, Angel C. Y. , Manichaikul, Ani , Montgomery, Courtney G. , Peloso, Gina M. , Roden, Dan M. , Weiss, Scott T. , Group, TOPMed Analysis Working, Abecasis, Gonçalo R.

Genetics | March 15, 2021 | Volume: 218 | Issue: 1 | Pages: No page available

10.1093/genetics/iyab044 | PMID 33720349 Get It

Abstract Traditional Hardy–Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.
Modeling autosomal dominant Alzheimer's disease with machine learning
Luckett, Patrick H. , McCullough, Austin , Gordon, Brian A. , Strain, Jeremy F. , Flores, Shaney , Dincer, Aylin , Kuffner, Todd A. , Stern, Ari, Meeker, Karin L. , Berman, Sarah , Chhatwal, Jasmeer P. , Cruchaga, Carlos , Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Xiong, Chengjie , Masters, Colin L. , Mori, Hiroshi , Noble, James M. , Salloway, Stephen , Cash, David M. , Fulham, Michael , Jack, Clifford R. , Vöglein, Jonathan , Klunk, William E. , Oh, Hwamee , Swisher, Laura, Marcus, Daniel S. , Koudelis, Deborah, Joseph‐Mathurin, Nelly , Cash, Lisa, Hornbeck, Russ C. , Perrin, Richard J. , Hassenstab, Jason , Morris, John C. , Bateman, Randall J. , (DIAN), for the Dominantly Inherited Alzheimer Network, Wang, Qing , Cruchaga, Carlos , Jack, Clifford R , Gordon, Brian A , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Joseph-Mathurin, Nelly , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Cash, David M , Berman, Sarah , McCarthy, John Edward , Jucker, Mathias , Schofield, Peter R. , Brickman, Adam M. , Brooks, William S. , Ghetti, Bernardino , Koeppe, Robert A. , Su, Yi , Weiner, Michael W. , Wáng, Qīng , Xiong, Chengjie , Karch, Celeste M. , McDade, Eric , Benzinger, Tammie L.S. , Ances, Beau M. , (DIAN), for the Dominantly Inherited Alzheimer Network, Noble, James M

Alzheimer's & Dementia | January 21, 2021 | Volume: 17 | Issue: 6 | Pages: 1005-1016

10.1002/alz.12259 | PMID 33480178 Get It

AbstractIntroductionMachine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.MethodsLongitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non‐carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status.ResultsThe Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non‐carriers.DiscussionResults suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.
Determining the recommended dose of pacritinib: results from the PAC203 dose-finding trial in advanced myelofibrosis
Gerds, Aaron T. , Savona, Michael R. , Scott, Bart L. , Egyed, Miklós , Harrison, Claire , Yacoub, Abdulraheem , Vannucchi, Alessandro M. , Mead, Adam J. , O’Sullivan, Jennifer , García‐Gutiérrez, Valentín , Rampal, Raajit K. , Miller, Carole B., Palmer, Jeanne , Buckley, Sarah , Mould, Diane R. , Ito, Kaori , Tyavanagimatt, Shanthakumar , Roman‐Torres, Karisse, Devineni, Sri, Craig, Adam R., Vannucchi, Alessandro M , Gerds, Aaron T , Savona, Michael R , Mead, Adam J , Talpaz, Moshe , Kiladjian, Jean‐Jacques , Bose, Prithviraj , Oh, Stephen T. , Smith, Jennifer A. , Mascarenhas, John

Blood Advances | December 3, 2020 | Volume: 4 | Issue: 22 | Pages: 5825-5835

10.1182/bloodadvances.2020003314 | PMID 33232476 Get It

Abstract PAC203 is a randomized dose-finding study of pacritinib, an oral JAK2/IRAK1 inhibitor, in patients with advanced myelofibrosis who are intolerant of or resistant to ruxolitinib. Patients were randomized 1:1:1 to pacritinib 100 mg once per day, 100 mg twice per day, or 200 mg twice per day. Enhanced eligibility criteria, monitoring, and dose modifications were implemented to mitigate risk of cardiac and hemorrhagic events. Efficacy was based on ≥35% spleen volume response (SVR) and ≥50% reduction in the 7-component total symptom score (TSS) through week 24. Of 161 patients, 73% were intolerant of and 76% had become resistant to ruxolitinib; 50% met criteria for both. Severe thrombocytopenia (platelet count <50 × 103/μL) was present in 44%. SVR rates were highest with 200 mg twice per day (100 mg once per day, 0%; 100 mg twice per day, 1.8%; 200 mg twice per day, 9.3%), particularly among patients with baseline platelet counts <50 × 103/μL (17%; 4 of 24). Although TSS response rate was similar across doses (100 mg once per day, 7.7%; 100 mg twice per day, 7.3%; 200 mg twice per day, 7.4%), median percent reduction in TSS suggested a dose-response relationship (–3%, −16%, and −27%, respectively). Pharmacokinetic and pharmacodynamic modeling based on all available data showed greatest SVR and TSS reduction at 200 mg twice per day compared with lower doses. Common adverse events were gastrointestinal events, thrombocytopenia, and anemia. There was no excess of grade ≥3 hemorrhagic or cardiac events at 200 mg twice per day. Pacritinib 200 mg twice per day demonstrated clinical activity and an acceptable safety profile and was selected as the recommended dose for a pivotal phase 3 study in patients with myelofibrosis and severe thrombocytopenia. This trial was registered at www.clinicaltrials.gov as #NCT03165734.
Single-subject grey matter network trajectories over the disease course of autosomal dominant Alzheimer’s disease
Vermunt, Lisa , Dicks, Ellen , Wang, Guoqiao , Dincer, Aylin , Flores, Shaney , Keefe, Sarah , Berman, Sarah , Cash, David M. , Chhatwal, Jasmeer P. , Cruchaga, Carlos , Fox, Nick C. , Graff‐Radford, Neill R. , Hassenstab, Jason , Laske, Christoph , Xiong, Chengjie , Masters, Colin L. , Mori, Hiroshi , Morris, John C. , Noble, James M. , Perrin, Richard J. , Visser, Pieter Jelle , Bateman, Randall J. , Gordon, Brian A. , (DIAN), Dominantly Inherited Alzheimer Network, Amtashar, Fatima, Bodge, Courtney, Brandon, Susan E. , Buck, Jill , Buckles, Virginia, Chea, Sochenda, Chrem, Patricio, Chui, Helena C., Cinco, Jake, Jack, Clifford, D’Mello, Mirelle , Donahue, Tamara, Douglas, Jane, Edigo, Noelia, Erekin-Taner, Nilufer, Fagan, Anne M. , Farlow, Marty, Farrar, Angela, Feldman, Howard , Flynn, Gigi, Franklin, Erin , Gant, Cortaiga, Gardener, Samantha L. , Gray, Julia, Gurney, Jenny , Hassenstab, Jason, Hirohara, Mie, Hornbeck, Russ C. , DiBari, Siri Houeland, Ikonomović, Snežana, Jerome, Gina, Klunk, William E. , Kuder-Buletta, Elke, Marcus, Daniel S. , Mason, Neal Scott, Maue-Dreyfus, Denise, Montoya, Lucy, Nagamatsu, Akem, Neimeyer, Katie, Norton, Joanne, Raichle, Marc, Ringman, John M. , Roh, Jee Hoon , Shiroto, Tomoyo, Sigurdson, Wendy, Sparks, Paige, Swisher, Laura, Taddei, Kevin , Wang, Peter, Weiner, Mike, Wolfsberger, Mary, Xiong, Chengjie, Tijms, Betty M , Gordon, Brian A , Cruchaga, Carlos , Bateman, Randall J , Masters, Colin L , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Roh, Jee Hoon , Cash, David M , Feldman, Howard H , Berman, Sarah , Ghetti, Bernardino , Karch, Celeste M. , McDade, Eric , Schofield, Peter R. , Xiong, Chengjie , Scheltens, Philip , Benzinger, Tammie L.S. , Tijms, Betty M. , (DIAN), Dominantly Inherited Alzheimer Network, Allegri, Ricardo , Brandon, Susan, Brooks, William S. , Buck, Jill, Chui, Helena C. , Fujii, Hisako , Goate, Alison , Goldman, Jill , Hassenstab, Jason, Holtzman, David M. , Ikeuchi, Takeshi , Jucker, Mathias , Kasuga, Kensaku , Kawarabayashi, Takeshi , Koeppe, Robert A. , Martins, Ralph N. , Shimada, Hiroyuki , Shoji, Mikio , Sohrabi, Hamid R. , Suzuki, Kazushi , Wang, Jen Chin C. , Xiong, Chengjie, Xu, Xiong, Noble, James M

Brain Communications | July 15, 2020 | Volume: 2 | Issue: 2 | Pages: No page available

10.1093/braincomms/fcaa102 | PMID 32954344 Get It

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.
Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer's disease
Schindler, Suzanne E. , Li, Yan , Todd, Kaitlin , Herries, Elizabeth, Henson, Rachel L. , Gray, Julia, Wang, Guoqiao , Graham, Danielle , Shaw, Leslie M. , Trojanowski, John Q. , Hassenstab, Jason , Benzinger, Tammie L.S. , Cruchaga, Carlos , Xiong, Chengjie , Chhatwal, Jasmeer P. , Noble, James M. , Ringman, John M. , Graff‐Radford, Neill R. , Ladenson, Jack H., Morris, John C. , Bateman, Randall J. , Fagan, Anne M. , Network, Dominantly Inherited Alzheimer, Fox, Nick C. , Cruchaga, Carlos , Bateman, Randall J , Xiong, Chengjie , Benzinger, Tammie L S , Fox, Nick C , Hassenstab, Jason , Morris, John C , Jucker, Mathias , Holtzman, David M. , Xiong, Chengjie , Network, Dominantly Inherited Alzheimer, Noble, James M

Alzheimer's & Dementia | March 4, 2019 | Volume: 15 | Issue: 5 | Pages: 655-665

10.1016/j.jalz.2018.12.019 | PMID 30846386 Get It

AbstractIntroductionFour less well‐studied but promising “emerging” cerebrospinal fluid (CSF) biomarkers are elevated in late‐onset Alzheimer disease (AD): neurogranin, synaptosomal‐associated protein‐25 (SNAP‐25), visinin‐like protein 1 (VILIP‐1), and chitinase‐3‐like protein 1 (YKL‐40).MethodsCSF neurogranin, SNAP‐25, VILIP‐1, and YKL‐40 were measured in families carrying autosomal‐dominant AD mutations.ResultsThe four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP‐25, VILIP‐1, and YKL‐40 were altered very early in the AD time course, approximately 15–19 years before estimated symptom onset. All CSF biomarkers predicted important AD‐related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset.DiscussionEarly abnormalities in CSF tTau, pTau, SNAP‐25, VILIP‐1, and YKL‐40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation.
Longitudinal analysis of epigenome-wide DNA methylation reveals novel smoking-related loci in African Americans
Liu, Jiaxuan , Zhao, Wei , Ammous, Farah , Mosley, Thomas H. , Zhou, Xiang , Smith, Jennifer A. , Zhao, Wei , Turner, Stephen T. , Zhou, Xiang , Smith, Jennifer A , Zhao, Wei

Epigenetics | February 15, 2019 | Volume: 14 | Issue: 2 | Pages: 171-184

10.1080/15592294.2019.1581589 | PMID 30764717 Get It

Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging
Jian, Xueqiu , Satizábal, Claudia L. , Smith, Albert V. , Wittfeld, Katharina , Bis, Joshua C. , Smith, Jennifer A. , Hofer, Edith , Mishra, Aniket , Adams, Hieab H.H. , Li, Shuo , Teumer, Alexander , Zhao, Wei , Saba, Yasaman , Yanek, Lisa R. , Chauhan, Ganesh , Buchem, Mark A. van , Royle, Natalie A., Niessen, Wiro J. , Windham, B. Gwen , DeStefano, Anita L. , Habes, Mohamad , Heckbert, Susan R. , Palmer, Nicholette D., Lewis, Cora E. , Eiríksdóttir, Guðný , Maillard, Pauline , Mathias, Rasika A. , Divers, Jasmin, Beiser, Alexa S., Langner, Sönke , Rice, Kenneth , Bastin, Mark E. , Starr, John M. , Sidney, Stephen , Risacher, Shannon L. , Uitterlinden, André G. , Guðnason, Vilmundur , Rotter, Jerome I. , Schreiner, Pamela J. , Boerwinkle, Eric , Duijn, Cornelia M. van , Sarnowski, Bettina von , Gottesman, Rebecca F., Levy, Daniel , Sigurðsson, Sigurður , Vernooij, Meike W. , Schmidt, Reinhold, Wardlaw, Joanna M. , Mosley, Thomas H. , DeCarli, Charles , Bowden, Donald W. , Becker, Diane M. , Deary, Ian J. , Schmidt, Helena , Kardia, Sharon L. R., Debette, Stéphanie , Longstreth, W.T. , Seshadri, Sudha , Launer, Lenore J. , Fornage, Myriam , Group, for the neuroCHARGE Working, Dichgans, Martin , Rice, Kenneth , Palmer, Nicholette D. , DeCarli, Charles , Turner, Stephen T. , Dichgans, Martin , Wardlaw, Joanna Marguerite , Smith, Jennifer A , Adams, Hieab H H , Satizabal, Claudia L , Seshadri, Sudha , Bastin, Mark E , Teumer, Alexander , van Duijn, Cornelia M , Debette, Stephanie , Smith, Albert V , Palmer, Nicholette D , Rotter, Jerome I , Mathias, Rasika A , Rice, Ken , Levy, Daniel , Hsu, Fang‐Chi , Nho, Kwangsik T. , Hagenaars, Saskia P. , Nyquist, Paul , Freedman, Barry I. , Cushman, Mary , Bryan, Robert Nick , Homuth, Georg , Hernández, Maria del Carmen Valdés , Divers, Jasmin , Yang, Qiong , Maldjian, Joseph A. , Nauck, Matthias A. , Mazoyer, Bernard , Psaty, Bruce M. , Saykin, Andrew J. , Ikram, M. Arfan , Grabe, Hans Jörgen , Group, for the neuroCHARGE Working, Maillard, Pauline

Stroke | July 12, 2018 | Volume: 49 | Issue: 8 | Pages: 1812-1819

10.1161/strokeaha.118.020689 | PMID 30002152 Get It

Background and Purpose— White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods— In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results— At 17q25, we confirmed the association of multiple common variants in TRIM65 , FBF1 , and ACOX1 ( P <6×10 −7 ). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; P EA =4.5×10 −8 ) partially independent of known common signal ( P EA(conditional) =1.4×10 −3 ). We further identified a locus at 2q33 containing common variants in NBEAL1 , CARF , and WDR12 (lead, rs2351524; P all =1.9×10 −10 ). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( P rs34136221 =2.8×10 −8 ). Conclusions— Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.
Association of urinary citrate excretion, pH, and net gastrointestinal alkali absorption with diet, diuretic use, and blood glucose concentration
Perinpam, Majuran, Smith, Jennifer A. , Kardia, Sharon L. R., Turner, Stephen T. , Smith, Jennifer A , Ware, Erin Bakshis , Lieske, John C.

Physiological Reports | October 17, 2017 | Volume: 5 | Issue: 19 | Pages: e13411

10.14814/phy2.13411 | PMID 29038354 Get It

Correction: The complex genetics of gait speed: genome-wide meta-analysis approach
Ben-Avraham, Dan, Karasik, David , Verghese, Joe , Lunetta, Kathryn L. , Eicher, John D., Vered, Rotem, Deelen, Joris , Arnold, Alice M. , Buchman, Aron S. , Faul, Jessica D. , Nethander, Maria , Fornage, Myriam , Adams, Hieab H.H. , Matteini, Amy M., Callisaya, Michele L. , Smith, Albert V. , Yu, Lei, Jager, Philip L. De , Evans, Denis A., Guðnason, Vilmundur , Hofman, Albert , Pattie, Alison, Knopman, Davis S., Parimi, Neeta, Bandinelli, Stefania , Beekman, Marian , Gutman, Danielle , Sharvit, Lital , Mooijaart, Simon P. , Liewald, David C. , Houwing‐Duistermaat, Jeanine J. , Ohlsson, Claes , Moed, Matthijs, Hernandez, Dena, Thomson, Russell , Tranah, Gregory J. , Weir, David R. , Zhao, Wei , Starr, John M. , Johnson, Andrew D. , Bennett, David A. , Cummings, Steven R. , Deary, Ian J. , Harris, Tamara B., Kardia, Sharon L. R., Mosley, Thomas H. , Srikanth, Velandai , Windham, B. Gwen , Davies, Gail , Evans, Daniel S. , Ferrucci, Luigi , Atzmon, Gil , Bennett, David A. , Turner, Stephen T. , Smith, Jennifer A. , Tanaka, Toshiko , Corley, Janie , Launer, Lenore J. , Verlinden, Vincentius J.A. , Mellström, Dan , Geest, Jos N. van der , Karlsson, Magnus K , McWhirter, Rebekah , Liu, Ching‐Ti , Uitterlinden, André G. , Ikram, M. Arfan , Newman, Anne B. , Walston, Jeremy D , Slagboom, P. Eline , Kiel, Douglas P. , Murabito, Joanne M. , Adams, Hieab H H , Smith, Albert V , Ferrucci, Luigi , Ohlsson, Claes , Srikanth, Velandai K

Aging | July 7, 2017 | Volume: 9 | Issue: 7 | Pages: 1844-1846

10.18632/aging.101260 | PMID 28696945 Get It