Literature DB >> 23110957

VETSA: the Vietnam Era Twin Study of Aging.

William S Kremen1, Carol E Franz, Michael J Lyons.   

Abstract

The Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study with a primary focus on cognitive and brain aging in men. It comprises a subset of over 1,200 twins from the Vietnam Era Twin Registry. Like many other studies of aging, the VETSA includes many different phenotypes, but there are some key features that distinguish it from most other behavioral genetic aging studies. First, the initial assessment was conducted when all participants were middle-aged. Second, the age range of participants is narrow; all were in their 50s at the time of the initial recruitment. Third, the study includes an extensive and demanding neurocognitive test battery that was designed to provide good coverage of different cognitive abilities and avoid ceiling effects in middle-aged adults. Fourth, young adult cognitive test data (at an average age of 20 years) are available to provide a gauge of cognitive change. These features make the VETSA ideal for studying the heterogeneity of within-individual trajectories from midlife to old age, and for early detection of risk factors for cognitive decline.

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Year:  2012        PMID: 23110957      PMCID: PMC3780387          DOI: 10.1017/thg.2012.86

Source DB:  PubMed          Journal:  Twin Res Hum Genet        ISSN: 1832-4274            Impact factor:   1.587


  25 in total

1.  Stability, growth, and decline in adult life span development of declarative memory: cross-sectional and longitudinal data from a population-based study.

Authors:  Michael Rönnlund; Lars Nyberg; Lars Bäckman; Lars-Göran Nilsson
Journal:  Psychol Aging       Date:  2005-03

2.  I. Longitudinal changes in aging brain function.

Authors:  L L Beason-Held; M A Kraut; S M Resnick
Journal:  Neurobiol Aging       Date:  2006-12-20       Impact factor: 4.673

3.  Genes, environment, and time: the Vietnam Era Twin Study of Aging (VETSA).

Authors:  William S Kremen; Heather Thompson-Brenner; Yat-Ming J Leung; Michael D Grant; Carol E Franz; Seth A Eisen; Kristen C Jacobson; Corwin Boake; Michael J Lyons
Journal:  Twin Res Hum Genet       Date:  2006-12       Impact factor: 1.587

Review 4.  The brain's default network: anatomy, function, and relevance to disease.

Authors:  Randy L Buckner; Jessica R Andrews-Hanna; Daniel L Schacter
Journal:  Ann N Y Acad Sci       Date:  2008-03       Impact factor: 5.691

5.  Does the capacity of working memory change with age?

Authors:  A Wingfield; E A Stine; C J Lahar; J S Aberdeen
Journal:  Exp Aging Res       Date:  1988 Summer-Autumn       Impact factor: 1.645

6.  Distinct genetic influences on cortical surface area and cortical thickness.

Authors:  Matthew S Panizzon; Christine Fennema-Notestine; Lisa T Eyler; Terry L Jernigan; Elizabeth Prom-Wormley; Michael Neale; Kristen Jacobson; Michael J Lyons; Michael D Grant; Carol E Franz; Hong Xian; Ming Tsuang; Bruce Fischl; Larry Seidman; Anders Dale; William S Kremen
Journal:  Cereb Cortex       Date:  2009-03-18       Impact factor: 5.357

7.  Cortical thickness is influenced by regionally specific genetic factors.

Authors:  Lars M Rimol; Matthew S Panizzon; Christine Fennema-Notestine; Lisa T Eyler; Bruce Fischl; Carol E Franz; Donald J Hagler; Michael J Lyons; Michael C Neale; Jennifer Pacheco; Michele E Perry; J Eric Schmitt; Michael D Grant; Larry J Seidman; Heidi W Thermenos; Ming T Tsuang; Seth A Eisen; William S Kremen; Anders M Dale
Journal:  Biol Psychiatry       Date:  2009-12-06       Impact factor: 13.382

8.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI.

Authors:  Michael D Greicius; Gaurav Srivastava; Allan L Reiss; Vinod Menon
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-15       Impact factor: 11.205

9.  Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study.

Authors:  William S Kremen; Elizabeth Prom-Wormley; Matthew S Panizzon; Lisa T Eyler; Bruce Fischl; Michael C Neale; Carol E Franz; Michael J Lyons; Jennifer Pacheco; Michele E Perry; Allison Stevens; J Eric Schmitt; Michael D Grant; Larry J Seidman; Heidi W Thermenos; Ming T Tsuang; Seth A Eisen; Anders M Dale; Christine Fennema-Notestine
Journal:  Neuroimage       Date:  2009-09-26       Impact factor: 6.556

10.  Genes determine stability and the environment determines change in cognitive ability during 35 years of adulthood.

Authors:  Michael J Lyons; Timothy P York; Carol E Franz; Michael D Grant; Lindon J Eaves; Kristen C Jacobson; K Warner Schaie; Matthew S Panizzon; Corwin Boake; Hong Xian; Rosemary Toomey; Seth A Eisen; William S Kremen
Journal:  Psychol Sci       Date:  2009-08-14
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  65 in total

1.  Neurodevelopmental origins of lifespan changes in brain and cognition.

Authors:  Kristine B Walhovd; Stine K Krogsrud; Inge K Amlien; Hauke Bartsch; Atle Bjørnerud; Paulina Due-Tønnessen; Håkon Grydeland; Donald J Hagler; Asta K Håberg; William S Kremen; Lia Ferschmann; Lars Nyberg; Matthew S Panizzon; Darius A Rohani; Jon Skranes; Andreas B Storsve; Anne Elisabeth Sølsnes; Christian K Tamnes; Wesley K Thompson; Chase Reuter; Anders M Dale; Anders M Fjell
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-18       Impact factor: 11.205

2.  Genetic and environmental architecture of changes in episodic memory from middle to late middle age.

Authors:  Matthew S Panizzon; Michael C Neale; Anna R Docherty; Carol E Franz; Kristen C Jacobson; Rosemary Toomey; Hong Xian; Terrie Vasilopoulos; Brinda K Rana; Ruth McKenzie; Michael J Lyons; William S Kremen
Journal:  Psychol Aging       Date:  2015-05-04

3.  Pupillary Responses as a Biomarker of Early Risk for Alzheimer's Disease.

Authors:  Eric L Granholm; Matthew S Panizzon; Jeremy A Elman; Amy J Jak; Richard L Hauger; Mark W Bondi; Michael J Lyons; Carol E Franz; William S Kremen
Journal:  J Alzheimers Dis       Date:  2017       Impact factor: 4.472

4.  Genetics and brain morphology.

Authors:  Lachlan T Strike; Baptiste Couvy-Duchesne; Narelle K Hansell; Gabriel Cuellar-Partida; Sarah E Medland; Margaret J Wright
Journal:  Neuropsychol Rev       Date:  2015-03-14       Impact factor: 7.444

5.  Genetic and environmental influences on mean diffusivity and volume in subcortical brain regions.

Authors:  Nathan A Gillespie; Michael C Neale; Donald J Hagler; Lisa T Eyler; Christine Fennema-Notestine; Carol E Franz; Michael J Lyons; Linda K McEvoy; Anders M Dale; Matthew S Panizzon; William S Kremen
Journal:  Hum Brain Mapp       Date:  2017-02-27       Impact factor: 5.038

6.  Cognitive ability in old age is predetermined by age 20 y.

Authors:  Denise C Park
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-30       Impact factor: 11.205

7.  Genetic and Environmental Associations Among Executive Functions, Trait Anxiety, and Depression Symptoms in Middle Age.

Authors:  Daniel E Gustavson; Carol E Franz; Matthew S Panizzon; Chandra A Reynolds; Hong Xian; Kristen C Jacobson; Rosemary Toomey; Michael J Lyons; William S Kremen
Journal:  Clin Psychol Sci       Date:  2018-11-13

8.  Conceptual and data-based investigation of genetic influences and brain asymmetry: a twin study of multiple structural phenotypes.

Authors:  Lisa T Eyler; Eero Vuoksimaa; Matthew S Panizzon; Christine Fennema-Notestine; Michael C Neale; Chi-Hua Chen; Amy Jak; Carol E Franz; Michael J Lyons; Wesley K Thompson; Kelly M Spoon; Bruce Fischl; Anders M Dale; William S Kremen
Journal:  J Cogn Neurosci       Date:  2013-11-27       Impact factor: 3.225

9.  The Genetic Association Between Neocortical Volume and General Cognitive Ability Is Driven by Global Surface Area Rather Than Thickness.

Authors:  Eero Vuoksimaa; Matthew S Panizzon; Chi-Hua Chen; Mark Fiecas; Lisa T Eyler; Christine Fennema-Notestine; Donald J Hagler; Bruce Fischl; Carol E Franz; Amy Jak; Michael J Lyons; Michael C Neale; Daniel A Rinker; Wesley K Thompson; Ming T Tsuang; Anders M Dale; William S Kremen
Journal:  Cereb Cortex       Date:  2014-02-18       Impact factor: 5.357

10.  Development and aging of cortical thickness correspond to genetic organization patterns.

Authors:  Anders M Fjell; Håkon Grydeland; Stine K Krogsrud; Inge Amlien; Darius A Rohani; Lia Ferschmann; Andreas B Storsve; Christian K Tamnes; Roser Sala-Llonch; Paulina Due-Tønnessen; Atle Bjørnerud; Anne Elisabeth Sølsnes; Asta K Håberg; Jon Skranes; Hauke Bartsch; Chi-Hua Chen; Wesley K Thompson; Matthew S Panizzon; William S Kremen; Anders M Dale; Kristine B Walhovd
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-02       Impact factor: 11.205

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