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Featured ArticleArticles, Behavioral/Cognitive

DRD4 Genotype Predicts Longevity in Mouse and Human

Deborah L. Grady, Panayotis K. Thanos, Maria M. Corrada, Jeffrey C. Barnett Jr., Valentina Ciobanu, Diana Shustarovich, Anthony Napoli, Alexandra G. Moyzis, David Grandy, Marcelo Rubinstein, Gene-Jack Wang, Claudia H. Kawas, Chuansheng Chen, Qi Dong, Eric Wang, Nora D. Volkow and Robert K. Moyzis
Journal of Neuroscience 2 January 2013, 33 (1) 286-291; https://doi.org/10.1523/JNEUROSCI.3515-12.2013
Deborah L. Grady
1Department of Biological Chemistry, College of Medicine, University of California, Irvine, California 92697,
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Panayotis K. Thanos
2Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, NIH, Bethesda, Maryland 20892,
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
4Department of Psychology, Stony Brook University, Stony Brook, New York 11794,
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Maria M. Corrada
5Department of Neurology, University of California, Orange, California 92868,
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Jeffrey C. Barnett Jr.
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
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Valentina Ciobanu
1Department of Biological Chemistry, College of Medicine, University of California, Irvine, California 92697,
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Diana Shustarovich
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
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Anthony Napoli
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
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Alexandra G. Moyzis
1Department of Biological Chemistry, College of Medicine, University of California, Irvine, California 92697,
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David Grandy
6Physiology and Pharmacology, Oregon Health Sciences University, Portland, Oregon, 97239,
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Marcelo Rubinstein
7Institute for Research on Genetic Engineering and Molecular Biology, National Council for Science and Technology (CONICET), C1428ADN Buenos Aires, Argentina,
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Gene-Jack Wang
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
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Claudia H. Kawas
5Department of Neurology, University of California, Orange, California 92868,
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Chuansheng Chen
8Department of Psychology and Social Behavior, University of California, Irvine, California 92697,
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Qi Dong
9National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, Peoples Republic of China,
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Eric Wang
1Department of Biological Chemistry, College of Medicine, University of California, Irvine, California 92697,
10Aria Diagnostics, Inc., San Jose, California 95138,
11Institute of Genomics and Bioinformatics, University of California, Irvine, California 92697, and
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Nora D. Volkow
2Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, NIH, Bethesda, Maryland 20892,
3Behavioral Neuropharmocology and Neuroimaging Laboratory, Medical Department, Brookhaven National Laboratory, Upton, New York 11973,
12National Institute on Drug Abuse, NIH, Bethesda, Maryland 20892
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Robert K. Moyzis
1Department of Biological Chemistry, College of Medicine, University of California, Irvine, California 92697,
9National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, Peoples Republic of China,
11Institute of Genomics and Bioinformatics, University of California, Irvine, California 92697, and
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    Figure 1.

    Survival curves of the oldest-old cohort. The known male (blue) and female (pink) survival curves of European ancestry individuals born in 1910 (the average birth year of participants) are shown (source: Berkeley Mortality Database, http://www.demog.berkeley.edu/∼bmd/; UK and USA data). Individuals older than 90 years of age represent 1.4% (male) to 2.9% (female) of their birth cohort. The projected curve of the 1995 birth cohort (orange) suggests that 17% of this cohort (males and females) will reach 90+ years of age (Social Security Administration, Alternative II Forecast, 1998, http://www.demog.berkeley.edu/∼bmd/). Inset, Diagrammatic representation of the human DRD4 gene region. Exon positions are indicated by blocks (yellow = noncoding; orange = coding), and the positions of alu repetitive sequences are represented by pointed blue blocks. The position of a coding 48 bp VNTR in exon 3 is indicated by a green triangle. The 2R to 11R variants of this repeat are indicated below exon 3, along with their frequencies in European ancestry populations (Ding et al., 2002; Grady et al., 2003; Wang et al., 2004; Grady et al., 2005; this study).

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    Figure 2.

    Comparison of expected to observed DRD4 genotypes. Oldest-old individuals (N = 310) were genotyped at the exon 3 DRD4 polymorphism (Fig. 1, inset) and compared with population-based European ancestry control sample DRD4 genotypes (Expected, N = 2902). The DRD4 7R/x category (black bars) contains individuals with at least one 7R (or derived 7R, i.e., 5R, 6R, 8R, 9R, 10R, and 11R) allele, and the non-7R/x category (striped bars) contains the remaining individuals. The expected and observed fraction for each category is shown. Expected 7R/x (N = 635), Non 7R/x (N = 2267); 90+ observed 7R/x (N = 113), Non 7R/x (N = 197); Female 7R/x (N = 86), Non 7R/x (N = 133); Male 7R/x (N = 27), Non 7R/x (N = 64). Asterisks denote observed differences significant at p = 3.5 × 10−9 (90+ years), p = 1.7 × 10−9 (Female), and p = 0.034 (Male) (see text).

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    Figure 3.

    DRD4 genotype and self-reported activity. The number of hours per day of activity reported in 1981 is plotted versus participants with a DRD4 7R/x genotype (black bars) or non-DRD4 7R/x genotype (striped bars). Comparisons are shown at the 5th, 25th, 50th, 75th, and 95th percentiles. Including DRD4 2R/x and 3R/x individuals with the DRD4 7R/x individuals instead of the non-7R/x individuals (Ding et al., 2002; Grady et al., 2003; Wang et al., 2004; Grady et al., 2005) gave comparable activity level differences (i.e., an ancestral 4R/4R vs non-4R/4R division).

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    Figure 4.

    Kaplan–Meier survival curves of mice as a function of genotype and exposure to an EE or DE. Insert, Lifespan per group (mean and SE). WT and HT mice reared in an EE lived significantly longer than when reared in a DE. In contrast, survival of DRD4 KO mice was not increased when reared in an EE compared with a DE and was shorter than that of WT and HT mice.

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    Figure 5.

    Spontaneous locomotor activity for different ages in WT, HT, and KO mice reared in a DE and an EE. Values correspond to means (±SE) and correspond to average activity over 90 min. The genotype-by-age interaction on locomotor activity was significant (F = 3.61, p < 0.001, ηp2 = 0.034) with overall significantly lower activity levels for KO mice than for WT or HT mice (p < 0.05). The interaction of environment by age with locomotor activity was also significant (F = 2.77, p = 0.017, ηp2 = 0.013); overall, DE mice were significantly more active than EE mice (p < 0.05). However, since animals in an EE decrease in spontaneous locomotor activity (Garland et al., 2011) and we did not record 24 h activity levels, we cannot compare activity levels across the two environmental conditions.

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The Journal of Neuroscience: 33 (1)
Journal of Neuroscience
Vol. 33, Issue 1
2 Jan 2013
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DRD4 Genotype Predicts Longevity in Mouse and Human
Deborah L. Grady, Panayotis K. Thanos, Maria M. Corrada, Jeffrey C. Barnett Jr., Valentina Ciobanu, Diana Shustarovich, Anthony Napoli, Alexandra G. Moyzis, David Grandy, Marcelo Rubinstein, Gene-Jack Wang, Claudia H. Kawas, Chuansheng Chen, Qi Dong, Eric Wang, Nora D. Volkow, Robert K. Moyzis
Journal of Neuroscience 2 January 2013, 33 (1) 286-291; DOI: 10.1523/JNEUROSCI.3515-12.2013

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DRD4 Genotype Predicts Longevity in Mouse and Human
Deborah L. Grady, Panayotis K. Thanos, Maria M. Corrada, Jeffrey C. Barnett Jr., Valentina Ciobanu, Diana Shustarovich, Anthony Napoli, Alexandra G. Moyzis, David Grandy, Marcelo Rubinstein, Gene-Jack Wang, Claudia H. Kawas, Chuansheng Chen, Qi Dong, Eric Wang, Nora D. Volkow, Robert K. Moyzis
Journal of Neuroscience 2 January 2013, 33 (1) 286-291; DOI: 10.1523/JNEUROSCI.3515-12.2013
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