Studies of health and longevity require accurate age reporting. Age misreporting among older adults in the United States is common.
Participants in the Long Life Family Study (LLFS) were matched to early-life census records. Age recorded in the census was used to evaluate age reporting in the LLFS. The study population was 99% non-Hispanic white.
About 88% of the participants were matched to 1910, 1920, or 1930 U.S. censuses. Match success depended on the participant’s education, place of birth, and the number of censuses available to be searched. Age at the time of the interview based on the reported date of birth and early-life census age were consistent for about 89% of the participants, and age consistency within 1 year was found for about 99% of the participants.
It is possible to match a high fraction of older study participants to their early-life census records when detailed information is available on participants’ family of origin. Such record linkage can provide an important source of information for evaluating age reporting among the oldest old participants. Our results are consistent with recent studies suggesting that age reporting among older whites in the United States appears to be quite good.
Age validation; Census; Centenarian; Longevity; Oldest old participants.
Sickle cell anemia is common in the Middle East and India where the HbS gene is sometimes associated with the Arab-Indian (AI) β-globin gene (HBB) cluster haplotype. In this haplotype of sickle cell anemia, fetal hemoglobin (HbF) levels are 3-4 fold higher than those found in patients with HbS haplotypes of African origin. Little is known about the genetic elements that modulate HbF in AI haplotype patients. We therefor studied Saudi HbS homozygotes with the AI haplotype (mean HbF 19.2±7.0%, range 3.6 to 39.6%) and known genotyped cis- and trans-acting elements associated with HbF expression. All cases, regardless of HbF concentration, were homozygous for AI haplotype-specific elements cis to HBB. SNPs in BCL11A and HBS1L-MYB that were associated with HbF in other populations explained only 8.8% of the variation of HbF. KLF1 polymorphisms associated previously with high HbF were not present In the 44 patients tested. The SNPs and genetic loci we have chosen for this study do not explain the high HbF in sickle cell patients with AI haplotype or its variation among patients with this haplotype. The dispersion of HbF levels among AI haplotype patients suggests that other genetic elements modulate the effects of the known cis- and trans-acting regulators. These regulatory elements, which remain to be discovered, might be specific in the Saudi and some other populations where HbF levels are especially high.
Motivation: Although several studies have used Bayesian classifiers for risk prediction using genome-wide single nucleotide polymorphism (SNP) datasets, no software can efficiently perform these analyses on massive genetic datasets and can accommodate multiple traits.
Results: We describe the program PleioGRiP that performs a genome-wide Bayesian model search to identify SNPs associated with a discrete phenotype and uses SNPs ranked by Bayes factor to produce nested Bayesian classifiers. These classifiers can be used for genetic risk prediction, either selecting the classifier with optimal number of features or using an ensemble of classifiers. In addition, PleioGRiP implements an extension to the Bayesian search and classification and can search for pleiotropic relationships in which SNPs are simultaneosly associated with two or more distinct phenotypes. These relationships can be used to generate connected Bayesian classifiers to predict the phenotype of interest either using genetic data alone or in combination with the secondary phenotype(s).
Availability: PleioGRiP is implemented in Java, and it is available from http://hdl.handle.net/2144/4367.
Supplementary data are available at Bioinformatics online.
Hypothesizing that members of families enriched for longevity delay morbidity compared to population controls and approximate the health-span of centenarians, we compared the health-spans of older generation subjects of the Long Life Family Study (LLFS) to controls without family history of longevity and to centenarians of the New England Centenarian Study (NECS) using Bayesian parametric survival analysis. We estimated hazard ratios, the ages at which specific percentiles of subjects had onsets of diseases, and the gain of years of disease-free survival in the different cohorts compared to referent controls. Compared to controls, LLFS subjects had lower hazards for cancer, cardiovascular disease, severe dementia, diabetes, hypertension, osteoporosis, and stroke. The age at which 20% of the LLFS siblings and probands had one or more age-related diseases was approximately 10 years later than NECS controls. While female NECS controls generally delayed the onset of age-related diseases compared with males controls, these gender differences became much less in the older generation of the LLFS and disappeared amongst the centenarians of the NECS. The analyses demonstrate extended health-span in the older subjects of the LLFS and suggest that this aging cohort provides an important resource to discover genetic and environmental factors that promote prolonged health-span in addition to longer life-span.
health-span; longevity; onset of disease; survival analysis; Weibull regression
Despite evidence from family studies that there is a strong genetic influence upon exceptional longevity, relatively few genetic variants have been associated with this trait. One reason could be that many genes individually have such weak effects that they cannot meet standard thresholds of genome wide significance, but as a group in specific combinations of genetic variations, they can have a strong influence. Previously we reported that such genetic signatures of 281 genetic markers associated with about 130 genes can do a relatively good job of differentiating centenarians from non-centenarians particularly if the centenarians are 106 years and older. This would support our hypothesis that the genetic influence upon exceptional longevity increases with older and older (and rarer) ages. We investigated this list of markers using similar genetic data from 5 studies of centenarians from the USA, Europe and Japan. The results from the meta-analysis show that many of these variants are associated with survival to these extreme ages in other studies. Since many centenarians compress morbidity and disability towards the end of their lives, these results could point to biological pathways and therefore new therapeutics to increase years of healthy lives in the general population.
centenarian; exceptional longevity; genetic association study; aging; gene; lifespan; meta-analysis
A mutation in the LMNA gene is responsible for the most dramatic form of premature aging, Hutchinson-Gilford progeria syndrome (HGPS). Several recent studies have suggested that protein products of this gene might have a role in normal physiological cellular senescence. To explore further LMNA's possible role in normal aging, we genotyped 16 SNPs over a span of 75.4 kb of the LMNA gene on a sample of long-lived individuals (US Caucasians with age ≥95 years, N=873) and genetically matched younger controls (N=443). We tested all common non-redundant haplotypes (frequency ≥ 0.05) based on subgroups of these 16 SNPs for association with longevity. The most significant haplotype, based on 4 SNPs, remained significant after adjustment for multiple testing (OR = 1.56, P=2.5×10−5, multiple-testing-adjusted P=0.0045). To attempt to replicate these results, we genotyped 3448 subjects from four independent samples of long-lived individuals and control subjects from 1) the New England Centenarian Study (NECS) (N=738), 2) the Southern Italian Centenarian Study (SICS) (N=905), 3) France (N=1103), and 4) the Einstein Ashkenazi Longevity Study (N=702). We replicated the association with the most significant haplotype from our initial analysis in the NECS sample (OR = 1.60, P=0.0023), but not in the other three samples (P>.15). In a meta-analysis combining all five samples, the best haplotype remained significantly associated with longevity after adjustment for multiple testing in the initial and follow-up samples (OR = 1.18, P=7.5×10−4, multiple-testing-adjusted P=0.037). These results suggest that LMNA variants may play a role in human lifespan.
longevity gene; human; longevity; genetics
Fetal hemoglobin (HbF) is a major modifier of disease severity in sickle cell anemia (SCA). Three major HbF quantitative trait loci (QTL) are known: the Xmn I site upstream of Gγ-globin gene (HBG2) on chromosome 11p15, BCL11A on chromosome 2p16, and HBS1L-MYB intergenic polymorphism (HMIP) on chromosome 6q23. However, the roles of these QTLs in SCA patients with uncharacteristically high HbF are not known. We studied 20 African American SCA patients with markedly elevated HbF (mean 17.2%). They had significantly higher minor allele frequencies (MAF) in two HbF QTLs, BCL11A and HMIP, compared with those with low HbF. A 3-bp (TAC) deletion in complete linkage disequilibrium (LD) with the minor allele of rs9399137 in HMIP was also present significantly more often in these patients. To further explore other genetic loci that might be responsible for this high HbF, we sequenced a 14.1 kb DNA fragment between the Aγ(HBG1) and δ-globin genes (HBD). Thirty-eight SNPs were found. Four SNPs had significantly higher major allele frequencies in the unusually high HbF group. In silico analyses of these 4 polymorphisms predicted alteration in transcription factor binding sites in 3.
Sickle cell anemia; Fetal hemoglobin; HbF quantitative trait loci
We analyze the relationship between age of survival, morbidity, and disability among centenarians (age 100–104 years), semisupercentenarians (age 105–109 years), and supercentenarians (age 110–119 years). One hundred and four supercentenarians, 430 semisupercentenarians, 884 centenarians, 343 nonagenarians, and 436 controls were prospectively followed for an average of 3 years (range 0–13 years). The older the age group, generally, the later the onset of diseases, such as cancer, cardiovascular disease, dementia, and stroke, as well as of cognitive and functional decline. The hazard ratios for these individual diseases became progressively less with older and older age, and the relative period of time spent with disease was lower with increasing age group. We observed a progressive delay in the age of onset of physical and cognitive function impairment, age-related diseases, and overall morbidity with increasing age. As the limit of human life span was effectively approached with supercentenarians, compression of morbidity was generally observed.
Centenarian; Supercentenarian; Compression of morbidity; Oldest old; Health span
Translational research generates and/or uses very large amounts of diverse data. Informatics principles and methods address datasets that are large and complex, whereas few translational researchers know these principles and methods and many cannot design, carry out, or analyze the results of these studies optimally. With few exceptions, informatics education has not been directed to researchers, especially established researchers. To fill this gap, we carried out a formal needs assessment of research informatics education of translational researchers, focusing on established researchers. Using the results, we developed a model curriculum for educating researchers in research informatics and a first generation model online course in research informatics for researchers. We are completing a formal evaluation of this online course with a diverse group of translational researchers. From the results of this evaluation, we will create a second version of the online course, a dissemination plan to make it available to researchers nationally, and a plan to enhance the course over time. We will discuss the implications for the future of translational research and research informatics.
The New England Centenarian Study (NECS) was founded in 1994 as a longitudinal study of centenarians to determine if centenarians could be a model of healthy human aging. Over time, the NECS along with other centenarian studies have demonstrated that the majority of centenarians markedly delay high mortality risk-associated diseases toward the ends of their lives, but many centenarians have a history of enduring more chronic age-related diseases for many years, women more so than men. However, the majority of centenarians seem to deal with these chronic diseases more effectively, not experiencing disability until well into their nineties. Unlike most centenarians who are less than 101 years old, people who live to the most extreme ages, e.g., 107+ years, are generally living proof of the compression of morbidity hypothesis. That is, they compress morbidity and disability to the very ends of their lives. Various studies have also demonstrated a strong familial component to extreme longevity and now evidence particularly from the NECS is revealing an increasingly important genetic component to survival to older and older ages beyond 100 years. It appears to us that this genetic component consists of many genetic modifiers each with modest effects, but as a group they can have a strong influence.
centenarians; genetic of longevity; heritability of longevity; compression of morbidity; genetic variation
Genome-wide association studies (GWAS) have identified numerous associations between genetic loci and individual phenotypes; however, relatively few GWAS have attempted to detect pleiotropic associations, in which loci are simultaneously associated with multiple distinct phenotypes. We show that pleiotropic associations can be directly modeled via the construction of simple Bayesian networks, and that these models can be applied to produce single or ensembles of Bayesian classifiers that leverage pleiotropy to improve genetic risk prediction. The proposed method includes two phases: (1) Bayesian model comparison, to identify Single-Nucleotide Polymorphisms (SNPs) associated with one or more traits; and (2) cross-validation feature selection, in which a final set of SNPs is selected to optimize prediction. To demonstrate the capabilities and limitations of the method, a total of 1600 case-control GWAS datasets with two dichotomous phenotypes were simulated under 16 scenarios, varying the association strengths of causal SNPs, the size of the discovery sets, the balance between cases and controls, and the number of pleiotropic causal SNPs. Across the 16 scenarios, prediction accuracy varied from 90 to 50%. In the 14 scenarios that included pleiotropically associated SNPs, the pleiotropic model search and prediction methods consistently outperformed the naive model search and prediction. In the two scenarios in which there were no true pleiotropic SNPs, the differences between the pleiotropic and naive model searches were minimal. To further evaluate the method on real data, a discovery set of 1071 sickle cell disease (SCD) patients was used to search for pleiotropic associations between cerebral vascular accidents and fetal hemoglobin level. Classification was performed on a smaller validation set of 352 SCD patients, and showed that the inclusion of pleiotropic SNPs may slightly improve prediction, although the difference was not statistically significant. The proposed method is robust, computationally efficient, and provides a powerful new approach for detecting and modeling pleiotropic disease loci.
pleiotropy; SNP; GWAS; prediction; Bayesian
The inheritance of genetic disease depends on ancestry that must be considered when interpreting genetic association studies and can provide insights when comparing traits in a population. We compared the genetic profiles of African Americans with sickle cell disease to those of Black Africans and Caucasian populations of European descent and found that they are less genetically admixed than other African Americans and have an ancestry similar to Yorubans, Mandenkas and Bantu.
sickle cell disease; genetic ancestry; admixture; genetic association
Despite the success of highly active antiretroviral therapy (HAART), HIV infected individuals remain at increased risk for frailty and declines in physical function that are more often observed in older uninfected individuals. This may reflect premature or accelerated muscle aging.
Skeletal muscle gene expression profiles were evaluated in three uninfected independent microarray datasets including young (19 to 29 years old), middle aged (40 to 45 years old) and older (65 to 85 years old) subjects, and a muscle dataset from HIV infected subjects (36 to 51 years old). Using Bayesian analysis, a ten gene muscle aging signature was identified that distinguished young from old uninfected muscle and included the senescence and cell cycle arrest gene p21/Cip1 (CDKN1A). This ten gene signature was then evaluated in muscle specimens from a cohort of middle aged (30 to 55 years old) HIV infected individuals. Expression of p21/Cip1 and related pathways were validated and further analyzed in a rodent model for HIV infection.
We identify and replicate the expression of a set of muscle aging genes that were prematurely expressed in HIV infected, but not uninfected, middle aged subjects. We validated select genes in a rodent model of chronic HIV infection. Because the signature included p21/Cip1, a cell cycle arrest gene previously associated with muscle aging and fibrosis, we explored pathways related to senescence and fibrosis. In addition to p21/Cip1, we observed HIV associated upregulation of the senescence factor p16INK4a (CDKN2A) and fibrosis associated TGFβ1, CTGF, COL1A1 and COL1A2. Fibrosis in muscle tissue was quantified based on collagen deposition and confirmed to be elevated in association with infection status. Fiber type composition was also measured and displayed a significant increase in slow twitch fibers associated with infection.
The expression of genes associated with a muscle aging signature is prematurely upregulated in HIV infection, with a prominent role for fibrotic pathways. Based on these data, therapeutic interventions that promote muscle function and attenuate pro-fibrotic gene expression should be considered in future studies.
Skeletal muscle; Aging; Gene expression; HIV infection; Senescence
Serum bilirubin levels have been associated with polymorphisms in the UGT1A1 promoter in normal populations and in patients with hemolytic anemias, including sickle cell anemia. When hemolysis occurs circulating heme increases, leading to elevated bilirubin levels and an increased incidence of cholelithiasis. We performed the first genome-wide association study (GWAS) of bilirubin levels and cholelithiasis risk in a discovery cohort of 1,117 sickle cell anemia patients. We found 15 single nucleotide polymorphisms (SNPs) associated with total bilirubin levels at the genome-wide significance level (p value <5×10−8). SNPs in UGT1A1, UGT1A3, UGT1A6, UGT1A8 and UGT1A10, different isoforms within the UGT1A locus, were identified (most significant rs887829, p = 9.08×10−25). All of these associations were validated in 4 independent sets of sickle cell anemia patients. We tested the association of the 15 SNPs with cholelithiasis in the discovery cohort and found a significant association (most significant p value 1.15×10−4). These results confirm that the UGT1A region is the major regulator of bilirubin metabolism in African Americans with sickle cell anemia, similar to what is observed in other ethnicities.
One of the most popular modeling approaches to genetic risk prediction is to use a summary of risk alleles in the form of an unweighted or a weighted genetic risk score, with weights that relate to the odds for the phenotype in carriers of the individual alleles. Recent contributions have proposed the use of Bayesian classification rules using Naïve Bayes classifiers. We examine the relation between the two approaches for genetic risk prediction and show that the methods are mathematically related. In addition, we study the properties of the two approaches and describe how they can be generalized to include various models of inheritance.
genetic risk prediction; genetic score; Naïve Bayes classifier; classification score; classification rule
Sickle cell anemia (SCA, HBB glu6val) is characterized by multiple complications and a high degree of phenotypic variability: some subjects have only sporadic pain crises and few acute hospitalizations, while others experience multiple serious complications, high levels of morbidity, and accelerated mortality. 1 The tumor necrosis factor-α (TNF-α) signaling pathway plays important roles in inflammation and the immune response; variation in this pathway might be expected to modify the overall severity of SCA through the pathway’s effects on the vascular endothelium.2, 3 We examined plasma biomarkers of TNF-α activity and endothelial cell activation for associations with SCA severity in 24 adults (12 mild, 12 severe). Two biomarkers, tumor necrosis factor-α receptor-1 (TNF-R1) and vascular cell adhesion molecule-1 (VCAM-1) were significantly higher in subjects with severe SCA. Along with these biomarker differences, we also examined data from a genome-wide association study (GWAS) using SCA severity as a disease phenotype, and found evidence of genetic association between disease severity and a single nucleotide polymorphism (SNP) in VCAM1, which codes for VCAM-1, and several SNPs in ARFGEF2, a gene involved in TNF-R1 release. 4
Sickle Cell Anemia; TNF-α; Disease Severity
Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different “genetic signatures” of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.
Supercentenarians (age 110+ years old) generally delay or escape age-related diseases and disability well beyond the age of 100 and this exceptional survival is likely to be influenced by a genetic predisposition that includes both common and rare genetic variants. In this report, we describe the complete genomic sequences of male and female supercentenarians, both age >114 years old. We show that: (1) the sequence variant spectrum of these two individuals’ DNA sequences is largely comparable to existing non-supercentenarian genomes; (2) the two individuals do not appear to carry most of the well-established human longevity enabling variants already reported in the literature; (3) they have a comparable number of known disease-associated variants relative to most human genomes sequenced to-date; (4) approximately 1% of the variants these individuals possess are novel and may point to new genes involved in exceptional longevity; and (5) both individuals are enriched for coding variants near longevity-associated variants that we discovered through a large genome-wide association study. These analyses suggest that there are both common and rare longevity-associated variants that may counter the effects of disease-predisposing variants and extend lifespan. The continued analysis of the genomes of these and other rare individuals who have survived to extremely old ages should provide insight into the processes that contribute to the maintenance of health during extreme aging.
whole genome sequence; genetics; longevity; centenarian; supercentenarian; aging
With the progressive aging of the human population, there is an inexorable decline in muscle mass, strength and function. Anabolic supplementation with testosterone has been shown to effectively restore muscle mass in both young and elderly men. In this study, we were interested in identifying serum factors that change with age in two distinct age groups of healthy men, and whether these factors were affected by testosterone supplementation.
We measured the protein levels of a number of serum biomarkers using a combination of banked serum samples from older men (60 to 75 years) and younger men (ages 18 to 35), as well as new serum specimens obtained through collaboration. We compared baseline levels of all biomarkers between young and older men. In addition, we evaluated potential changes in these biomarker levels in association with testosterone dose (low dose defined as 125 mg per week or below compared to high dose defined as 300 mg per week or above) in our banked specimens.
We identified nine serum biomarkers that differed between the young and older subjects. These age-associated biomarkers included: insulin-like growth factor (IGF1), N-terminal propeptide of type III collagen (PIIINP), monokine induced by gamma interferon (MIG), epithelial-derived neutrophil-activating peptide 78 (ENA78), interleukin 7 (IL-7), p40 subunit of interleukin 12 (IL-12p40), macrophage inflammatory protein 1β (MIP-1β), platelet derived growth factor β (PDGFβ) and interferon-inducible protein 10 (IP-10). We further observed testosterone dose-associated changes in some but not all age related markers: IGF1, PIIINP, leptin, MIG and ENA78. Gains in lean mass were confirmed by dual energy X-ray absorptiometry (DEXA).
Results from this study suggest that there are potential phenotypic biomarkers in serum that can be associated with healthy aging and that some but not all of these biomarkers reflect gains in muscle mass upon testosterone administration.
Testosterone; Age; Biomarker
microRNA (miRNA) are short, noncoding RNA that negatively regulate gene expression and may play a causal role in invasive breast cancer. Since many genetic aberrations of invasive disease are detectable in early stages, we hypothesized that miRNA expression dysregulation and the predicted changes in gene expression might also be found in early breast neoplasias.
Expression profiling of 365 miRNA by real-time quantitative polymerase chain reaction assay was combined with laser capture microdissection to obtain an epithelium-specific miRNA expression signature of normal breast epithelium from reduction mammoplasty (RM) (n = 9) and of paired samples of histologically normal epithelium (HN) and ductal carcinoma in situ (DCIS) (n = 16). To determine how miRNA may control the expression of codysregulated mRNA, we also performed gene expression microarray analysis in the same paired HN and DCIS samples and integrated this with miRNA target prediction. We further validated several target pairs by modulating the expression levels of miRNA in MCF7 cells and measured the expression of target mRNA and proteins.
Thirty-five miRNA were aberrantly expressed between RM, HN and DCIS. Twenty-nine miRNA and 420 mRNA were aberrantly expressed between HN and DCIS. Combining these two data sets with miRNA target prediction, we identified two established target pairs (miR-195:CCND1 and miR-21:NFIB) and tested several novel miRNA:mRNA target pairs. Overexpression of the putative tumor suppressor miR-125b, which is underexpressed in DCIS, repressed the expression of MEMO1, which is required for ErbB2-driven cell motility (also a target of miR-125b), and NRIP1/RIP140, which modulates the transcriptional activity of the estrogen receptor. Knockdown of the putative oncogenic miRNA miR-182 and miR-183, both highly overexpressed in DCIS, increased the expression of chromobox homolog 7 (CBX7) (which regulates E-cadherin expression), DOK4, NMT2 and EGR1. Augmentation of CBX7 by knockdown of miR-182 expression, in turn, positively regulated the expression of E-cadherin, a key protein involved in maintaining normal epithelial cell morphology, which is commonly lost during neoplastic progression.
These data provide the first miRNA expression profile of normal breast epithelium and of preinvasive breast carcinoma. Further, we demonstrate that altered miRNA expression can modulate gene expression changes that characterize these early cancers. We conclude that miRNA dysregulation likely plays a substantial role in early breast cancer development.
editorial; genetics; risk factors
Individuals from families recruited for the Long Life Family Study (LLFS) (n= 4559) were examined and compared to individuals from other cohorts to determine whether the recruitment targeting longevity resulted in a cohort of individuals with better health and function. Other cohorts with similar data included the Cardiovascular Health Study, the Framingham Heart Study, and the New England Centenarian Study. Diabetes, chronic pulmonary disease and peripheral artery disease tended to be less common in LLFS probands and offspring compared to similar aged persons in the other cohorts. Pulse pressure and triglycerides were lower, high density lipids were higher, and a perceptual speed task and gait speed were better in LLFS. Age-specific comparisons showed differences that would be consistent with a higher peak, later onset of decline or slower rate of change across age in LLFS participants. These findings suggest several priority phenotypes for inclusion in future genetic analysis to identify loci contributing to exceptional survival.
longevity; exceptional survival; family studies; genetics; healthy aging; genome wide association study; multicenter studies; aging phenotypes
Family studies of exceptional longevity can potentially identify genetic and other factors contributing to long life and healthy aging. Although such studies seek families that are exceptionally long lived, they also need living members who can provide DNA and phenotype information. On the basis of these considerations, the authors developed a metric to rank families for selection into a family study of longevity. Their measure, the family longevity selection score (FLoSS), is the sum of 2 components: 1) an estimated family longevity score built from birth-, gender-, and nation-specific cohort survival probabilities and 2) a bonus for older living siblings. The authors examined properties of FLoSS-based family rankings by using data from 3 ongoing studies: the New England Centenarian Study, the Framingham Heart Study, and screenees for the Long Life Family Study. FLoSS-based selection yields families with exceptional longevity, satisfactory sibship sizes and numbers of living siblings, and high ages. Parameters in the FLoSS formula can be tailored for studies of specific populations or age ranges or with different conditions. The first component of the FLoSS also provides a conceptually sound survival measure to characterize exceptional longevity in individuals or families in various types of studies and correlates well with later-observed longevity.
aged, 80 and over; family data; longevity; Shannon information