Age-Related Biomarkers in LLFS Families With Exceptional Cognitive Abilities.
BACKGROUND
We previously demonstrated familial aggregation of memory performance within the Long Life Family Study (LLFS), suggesting that exceptional cognition (EC) may contribute to their exceptional longevity. Here, we investigated whether LLFS families with EC may also exhibit more favorable profiles of other age-related biomarkers.


METHODS
Nondemented offspring of the LLFS probands scoring 1.5 SD above the mean in a cognitive phenotype were classified as participants with EC. Families were categorized into EC (n = 28) and non-EC families (n = 433) based on having at least two EC offspring. Adjusted general estimating equations were used to investigate whether EC families had a better longevity and age-related biomarker profiles than non-EC families.


RESULTS
EC families exhibited higher scores on familial longevity than non-EC families (average Family Longevity Selection Score of 12 ± 7 vs 9 ± 8, p = 2.5 × 10-14). EC families showed a better a metabolic profile (β = -0.63, SE = 0.23, p = .006) than non-EC families. The healthier metabolic profile is related to obesity in an age-dependent fashion. The prevalence of obesity in EC families is significantly lower compared with non-EC families (38% vs 51%, p = .015) among family members less than 80 years of age; however, among EC family members 80 years of age and older, the prevalence of obesity is higher (40% vs 38%, p = .011). EC families also showed better physical/pulmonary function than non-EC families (β = 0.51, SE = 0.25, p = .042).


CONCLUSIONS
Long-live families with EC are characterized by a healthier metabolic profile which is related to the prevalence of obesity in the older family members. Our results suggest that familial exceptional longevity may be achieved through heterogeneous yet correlated pathways.
G.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Sandra
S
Barral
Departments of Epidemiology and of Human Genetics, Center for Aging and Population Health University of Pittsburgh, Pennsylvania.
Jatinder
J
Singh
G.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Erin
E
Fagan
G.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Stephanie
S
Cosentino
Section of Geriatrics, Department of Medicine, Boston Medical Center, Boston, University School of Medicine, Massachusetts.
Stacy L
SL
Andersen-Toomey
Division of Biostatistics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Mary K
MK
Wojczynski
Division of Biostatistics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Mary
M
Feitosa
Departments of Epidemiology and of Human Genetics, Center for Aging and Population Health University of Pittsburgh, Pennsylvania.
Candace M
CM
Kammerer
G.H. Sergievsky Center, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, New York.
Nicole
N
Schupf
D000367:Age Factors; D000368:Aged; D015415:Biomarkers; D003071:Cognition / Q000502:physiology*; D005260:Female; D006801:Humans; D008136:Longevity / Q000235:genetics / Q000502:physiology*; D008297:Male; D008875:Middle Aged
D015415:Biomarkers
Age-related biomarkers; Exceptional cognition; Exceptional longevity