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Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P

Background Serum levels of insulin-like growth factor 1 (IGF-1) and body mass index (BMI) are both associated with susceptibility to age-related diseases. Reports on the correlation between them have been conflicting, with both positive to negative correlations reported. However, the age ranges of the participants varied widely among these studies. Methods Using data on 4241 participants (aged 24–110) from the Long Life Family Study, we investigated the relationship between IGF-1 and BMI by age groups using regression analysis. Results When stratified by age quartile, the relationship between IGF-1 and BMI varied: in the first quartile (Q1, 20–58 years) the relationship was negative (β = −0.2, p = .002); in Q2 (58–66 years) and Q3 (67–86 years) the relationship was negative (β = −0.07, β = −0.01, respectively) but nonsignificant; and in Q4 (87–110 years) the relationship was positive (β = 0.31, p = .0002). This pattern did not differ by sex. We observed a similar age-related pattern between IGF-1 and BMI among participants in the third National Health and Nutritional Examination Survey. Conclusions Our results that the relationship between IGF-1 and BMI differs by age may explain some of the inconsistency in reports about their relationship and encourage additional studies to understand the mechanisms underlying it.

Background The Long Life Family Study (LLFS) enrolled families exhibiting exceptional longevity. The goal of this article was to determine the prevalence and predictors of remaining independent after 7 years in the oldest generation. Methods We examined 7-year change in physical (free of activities of daily living difficulty), cognitive (Mini-Mental State Examination score ≥ 24), and overall independence (physically/cognitively independent) in adults aged 90.3 ± 6.3 from LLFS’s oldest generation. Potential predictors (n = 28) of remaining independent included demographics, diseases, biomarkers, anthropometrics, and physical and cognitive performance tasks and were determined using generalized estimating equations (α: p < .05). This was a discovery/exploratory analysis, so no multiple testing correction was employed and the results require independent replication. Results At baseline (n = 1442), 67.3%, 83.8%, and 79.7% were overall, physically, and cognitively independent, respectively. After 7 years, 66% died, 7.5% were lost to follow-up, and the prevalence of overall independence decreased to 59.1% in survivors (−8.2%, 95% confidence interval: −14.1%, 2.2%). Of those with baseline independence, 156/226 (69.0%) remained independent. Predictors of remaining physically independent included younger age, better Short Physical Performance Battery score and lung function, smaller waist circumference, and lower soluble receptor for advanced glycation end-product levels (p < .05). Predictors of remaining cognitively independent included no cancer history, better Digit Symbol Substitution Test performance, and higher body weight (p < .05). Conclusions The prevalence of independence decreased by only 8.2% after 7 years, demonstrating the close correspondence between disability and mortality. Further, despite a mean baseline age of 90 years, a large proportion of survivors remained independent, suggesting this exceptional subgroup may harbor protective mechanisms.

Age is major risk factor for AD; however, relationships between aging and AD are not well understood. Decline in physiological resilience is universal feature of human aging that may also play role in AD. Aging-related pathways (such as IGF-I/P53/mTOR-mediated) that are involved in tissue resilience work in concert to decide outcomes of cell responses to stress/damage, such as survival, apoptosis, autophagy, etc. We hypothesized that interplay among genes in these pathways may influence AD risk as result of epistasis (GxG). We estimated effects of pairwise epistasis between SNPs in 53 genes from respective pathways on AD risk in the LLFS compared with other data (HRS, CHS, LOADFS). We found significant (fdr

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.

Experimental and clinical studies of Alzheimer’s disease (AD) provide plentiful evidence of AD heterogeneity and involvement of many interacting genes and pathways in regulation of AD-related traits. However, detailed mechanisms of genetic interactions (GxG) involved in AD remain largely unknown. Uncovering hidden patterns of such interactions from human data will help better understand the nature of AD heterogeneity and find new targets for AD prevention. In this paper, we applied a newly developed method of evaluating joint GxG effects on AD to analysis of the Long Life Family Study data. The analysis included several steps: (i) selecting candidate genes from stress response pathways that are thought to be involved in AD; (ii) estimating interaction effects of SNP-pairs on AD risk, and selecting the top interacting SNPs; (iii) running GWAS-like interaction analysis for SNP-pairs, with one SNP fixed; (iv) using characteristics of the detected SNP-pairs interactions to construct the SNP-specific Interaction Polygenic Risk Scores (IPRS); and (v) evaluating the effects of IPRSs on AD. We found that SNP-specific IPRS have highly significant effects on AD risk. For most SNPs involved in the significant interaction effects on AD, their individual effects were statistically not significant. Male and female analyses yielded different subsets of the top interacting SNPs. These results support major role of genetic interactions in heterogeneity of AD, and indicate that AD mechanisms can involve different combinations of the interacting genetic variants in males and females, which may point to different pathways of resistance/response to stressors in two genders.

Serum levels of insulin-like growth factor 1 (IGF-1) and measures of adiposity, such as body mass index (BMI), are associated with susceptibility to age-related diseases. Previous reports of the relationship between IGF-1 and BMI ranged from positive to negative to no relationship, perhaps because previous reports studied different age cohorts. Using data on 4270 participants (aged 24-110 years) from the Long Life Family Study, we investigated the relationship between IGF-1 and BMI overall and by age groups. IGF-1 and BMI were positively correlated in the total sample (β=0.161, r2= 0.0038, p=1.8-05). However, further analyses revealed that the relationship between IGF-1 and BMI varied by age quartile: in the 1st quartile (24-58yo) the relationship was negative (β=−0.204, r2= 0.011, p=0.0008); in the 2nd quartile (59-66yo) the relationship was negative but non-significant (β=−0.069, r2= 0.0012, p=0.28); in the 3rd quartile (67-86yo) the relationship was positive but non-significant (β=0.106, r2= 0.002, p=0.13); and in the 4th quartile (87-110yo) the relationship was positive (β=0.388, r2= 0.019, p=1.2−05). This pattern did not differ by sex. We also detected a similar age-related pattern between IGF-1 and BMI using an independent dataset (NHANES III), comprising 2550 men and women aged 20-90 years. Our results may clarify some of the inconsistency in previous literature about the relationship between IGF-1 and BMI. Additional studies of IGF-1 and adiposity measures are needed to better understand the underlying mechanisms involved.

Genetic influences on lipid traits have been suggested by numerous studies. In addition to heritability studies, over 50 genome scans have been performed to identify regions of linkage for quantitative lipid levels. Five of these scans have been performed in African Americans (four univariate and one bivariate linkage analysis), but with results that have been largely inconclusive. Linkage analyses are often limited by both sample size and heterogeneity, which may lead to nominal LOD scores or lack of evidence for linkage; the use of meta-analysis to combine linkage results from populations with similar ethnic backgrounds may help overcome some of these limitations. Thus, we performed a meta-analysis using data from four genome scans conducted in African American families to identify chromosomal regions showing evidence of linkage for total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL) and high density lipoprotein cholesterol (HDL). Significant evidence (i.e. P