Candidate gene resequencing to identify rare, pedigree-specific variants influencing healthy aging phenotypes in the long life family study

NIA Long Life Family Study: Objectives, Design, and Heritability of Cross Sectional and Longitudinal Phenotypes

The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006–2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014–2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families.

Signaling pathways associated with structural changes in varicose veins: a case-control study

INTRODUCTION AND OBJECTIVES

In varicose veins, blood pressure increases in the veins of the lower extremities due to mechanical stimulation and function remodeling. The aim of this study is assessment of Signaling pathways associated with structural changes in varicose veins.

MATERIALS AND METHODS

This pilot study was performed on patients with varicose veins, which had undergone surgery. The healthy tissues from trauma patients or vascular bypass without underlying diseases were used for control samples. Hematoxylin-eosin, trichrome, and elastin staining were used for histopathological examination. The levels of MDA (malondialdehyde), total thiol, SOD (Superoxide dismutase) and NO (nitric oxide) level were measured using Elisa kits to evaluate the oxidative stress level. Gene expression levels of MMP2, MMP9, FOXO3a, APOE and p53 genes were determined using Real-time PCR.

RESULTS

This study showed, the vascular Vein wall changes are visible in vascular collagen staining. Although these changes are observed in the structure of vascular wall collagen fibers, the accumulation of collagen and elastin was increased in the walls of varicose veins compared to the control group. The amount of nitric oxide and thiol were increased in the varicose group (P < 0.0001). The expression of metalloproteinase2 gene associated with extracellular matrix change was increased in varicose veins. However, the amount of metalloproteinase 9 was decreased in this group compared to control group. FOXO3a, APOE Genes were down-regulated in the varicose veins compared to control group, while p53 gene expression was significantly increased in the varicose group (P < 0.0001).

CONCLUSION

This study demonstrated changes in oxidative stress, morphological structure, and aging pathways in varicose when compared to non-varicose veins. The changes in oxidative stress may be associated with the variations in morphological structure and aging pathways which contribute to the pathogenesis of varicose veins.

TIP60 in aging and neurodegeneration

Epigenetic modification of chromatin, including histone methylation and acetylation, plays critical roles in eukaryotic cells and has a significant impact on chromatin structure/accessibility, gene regulation and, susceptibility to aging, neurodegenerative disease, cancer, and other age-related diseases. This article reviews the current advances on TIP60/KAT5, a major histone acetyltransferase with diverse functions in eukaryotes, with emphasis on its regulation of autophagy, proteasome-dependent protein turnover, RNA transcription, DNA repair, circadian rhythms, learning and memory, and other neurological functions implicated in aging and neurodegeneration. Moreover, the promising therapeutic potential of TIP60 is discussed to target Alzheimer's disease and other neurological diseases.

Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants

BACKGROUND

Longevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB).

METHODS

From an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (<.01 population frequency) variants shared by at least one elderly cousin pair in a region likely to be identical by descent were identified as candidates. Ingenuity Variant Analysis was used to prioritize putative causal variants based on quality control, frequency, and gain or loss of function. The variant frequency was compared in healthy cohorts and in an Alzheimer's disease cohort. Remaining variants were filtered based on their presence in genes reported to have an effect on the aging process, aging of cells, or the longevity process. Validation of these candidate variants included tests of segregation on other elderly relatives.

RESULTS

Fifteen rare candidate genetic variants spanning 17 genes shared within cousins were identified as having passed prioritization criteria. Of those variants, six were present in genes that are known or predicted to affect the aging process: rs78408340 (PAM), rs112892337 (ZFAT), rs61737629 (ESPL1), rs141903485 (CEBPE), rs144369314 (UTP4), and rs61753103 (NUP88 and RABEP1). ESPL1 rs61737629 and CEBPE rs141903485 show additional evidence of segregation with longevity in expanded pedigree analyses (p-values = .001 and .0001, respectively).

DISCUSSION

This unique pedigree analysis efficiently identified several novel rare candidate variants that may affect the aging process and added support to seven genes that likely contribute to longevity. Further analyses showed evidence for segregation for two rare variants, ESPL1 rs61737629 and CEBPE rs141903485, in the original longevity pedigrees in which they were initially observed. These candidate genes and variants warrant further investigation.

Network Pharmacology-Based Strategy to Investigate the Pharmacological Mechanisms of Ginkgo biloba Extract for Aging

Aging is a main risk factor for a number of debilitating diseases and contributes to an increase in mortality. Previous studies have shown that Ginkgo biloba extract (EGb) can prevent and treat aging-related diseases, but its pharmacological effects need to be further clarified. This study aimed to propose a network pharmacology-based method to identify the therapeutic pathways of EGb for aging. The active components of EGb and targets of sample chemicals were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. Information on aging-related genes was obtained from the Human Ageing Genomic Resources database and JenAge Ageing Factor Database. Subsequently, a network containing the interactions between the putative targets of EGb and known therapeutic targets of aging was established, which was used to investigate the pharmacological mechanisms of EGb for aging. A total of 24 active components, 154 targets of active components of EGb, and 308 targets of aging were obtained. Network construction and pathway enrichment were conducted after data integration. The study found that flavonoids (quercetin, luteolin, and kaempferol) and beta-sitosterol may be the main active components of EGb. The top eight candidate targets, namely, PTGS2, PPARG, DPP4, GSK3B, CCNA2, AR, MAPK14, and ESR1, were selected as the main therapeutic targets of EGb. Pathway enrichment results in various pathways were associated with inhibition of oxidative stress, inhibition of inflammation, amelioration of insulin resistance, and regulation of cellular biological processes. Molecular docking results showed that PPARG had better binding capacity with beta-sitosterol, and PTGS2 had better binding capacity with kaempferol and quercetin. The main components of EGb may act on multiple targets, such as PTGS2, PPARG, DPP4, and GSK3B, to regulate multiple pathways, and play an antiaging role by inhibiting oxidative stress, inhibiting inflammation, and ameliorating insulin resistance.

SYNE1-QK1 SNPs, G × G and G × E interactions on the risk of hyperlipidaemia

This study aimed to assess the relationship of 3 spectrin repeat containing nuclear envelope protein 1 (SYNE1) and 4 KH domain containing RNA binding (QK1) single nucleotide polymorphisms (SNPs), their haplotypes, gene‐gene (G × G), gene‐environment (G × E) interactions and hypercholesterolaemia (HCH) and hypertriglyceridaemia (HTG) in the Chinese Maonan minority. The genetic make‐up of the SYNE1‐QK1 SNPs in 1932 unrelated subjects (normal, 641; HCH, 649; and HTG, 642) was obtained by next‐generation sequencing technologies. The genotypic frequencies of following SNPs were suggestively distinctive between the control and HCH groups (rs2623963, rs7745725, rs9459317, rs16897566), or between the control and HTG groups (rs2623963, rs1358317, rs7745725, rs1923608, rs16897566 SNPs; P < .05, respectively). Multiple‐locus linkage disequilibrium analysis indicated that the identified SNPs were not inherited independently. Several haplotypes and gene‐gene interaction haplotypes among the detected SNPs may be related with an increased morbidity of HCH (C‐G‐A, C‐G‐G and C‐G‐G‐T‐C‐A‐T) and HTG (C‐G‐G, G‐T‐G‐C, C‐G‐G‐G‐T‐G‐C and C‐G‐G‐T‐C‐A‐T), whereas others may be related with an decreased risk of HCH (G‐A‐A, G‐C‐A‐T, C‐A‐A‐T‐C‐A‐T and G‐A‐A‐G‐C‐A‐T) and HTG (G‐A‐A, G‐C‐A‐T, C‐A‐A‐T‐C‐A‐T and G‐A‐A‐G‐C‐A‐T). The association evaluation based on haplotypes and gene‐gene interactions could improve the power of detecting the risk of dyslipidaemia than anyone of SNP alone. There was significant three‐locus model involving SNP‐SNP, haplotype‐haplotype/environment and G × G interactions (P < .05‐0.001) that were detected by GMDR in HCH and HTG groups. Different interactions between genetic and environmental factors would produce different redundancy or synergy effects on the morbidity of HCH and/or HTG.

Prevalence of clinically actionable disease variants in exceptionally long-lived families

Background

Phenotypic expression of pathogenic variants in individuals with no family history of inherited disorders remains unclear.

Methods

We evaluated the prevalence of pathogenic variants in 25 genes associated with Mendelian-inherited disorders in 3015 participants from 485 families in the Long Life Family Study (LLFS). Boot-strapping and Fisher’s exact test were used to determine whether allele frequencies in LLFS were significantly different from the allele frequencies reported in publicly available genomic databases.

Results

The proportions of pathogenic autosomal dominant mutation carriers in BRCA1 and SDHC in LLFS study participants were similar to those reported in publicly available genomic databases (0.03% vs. 0.0008%, p = 1 for BRCA1, and 0.08% vs. 0.003%, p = 0.05 for SDHC). The frequency of carriers of pathogenic autosomal recessive variants in CPT2, ACADM, SUMF1, WRN, ATM, and ACADVL were also similar in LLFS as compared to those reported in genomic databases. The lack of clinical disease among LLFS participants with well-established pathogenic variants in BRCA1 and SDHC suggests that penetrance of pathogenic variants may be different in long lived families.

Conclusion

Further research is needed to better understand the penetrance of pathogenic variants before expanding large scale genomic testing to asymptomatic individuals.

Effect of Intentional Weight Loss on Mortality Biomarkers in Older Adults With Obesity

BACKGROUND

Observational research has identified several mortality biomarkers; however, their responsiveness to change is unknown. We tested whether the Healthy Aging Index (HAI) and other mortality biomarkers were responsive to intentional weight loss (WL), which is associated with lower mortality risk in recent meta-analyses.

METHODS

Older adults (70.3 ± 3.7 years) with obesity were randomized into a 6-month WL (n = 47) or weight stability (WS: ±5% baseline weight; n = 48) program. Baseline and 6-month HAI score (0-10) was calculated from component sum (each 0-2: systolic blood pressure, forced vital capacity [FVC], creatinine, fasting blood glucose [FBG], Montreal Cognitive Assessment), and gait speed, grip strength, Digit Symbol Substitution Test, FEV1, Interleukin-6, C-Reactive Protein, and Cystatin-C were assessed at baseline and 6 months.

RESULTS

Mean baseline HAI was 3.2 ± 1.6. By 6 months, WL participants lost 8.87 (95% CI: -10.40, -7.34) kg, whereas WS participants remained weight stable. WL group reduced HAI score (WL: -0.75 [95% CI: -1.11, -0.39] vs WS: -0.22 [95% CI: -0.60, 0.15]; p = .04), and components changing the most were FBG (WL: -3.89 [95% CI: -7.78, 0.00] mg/dL vs WS: 1.45 [95% CI: -2.61, 5.50] mg/dL; p = .047) and FVC (WL: 0.11 [95% CI: -0.01, 0.23] L vs WS: -0.05 [95% CI: -0.17, 0.08] L; p = .06). Among other biomarkers, only Cystatin-C significantly changed (WL: -2.53 [95% CI: -4.38, -0.68] ng/mL vs WS: 0.07 [95% CI: -1.85, 1.98] ng/mL; p = .04). Combining treatment groups, 1 kg WL was associated with a 0.07 (95% CI: 0.03, 0.12) HAI reduction (p < .01).

CONCLUSION

Intentional WL via caloric restriction reduced HAI score by 0.53 points, largely attributable to metabolic and pulmonary improvements.

Genetic and epigenetic regulation of human aging and longevity

Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.

Neuropsychology of aging

All people want to age "successfully," maintaining functional capacity and quality of life as they reach advanced age. Achieving this goal depends on preserving optimal cognitive and brain functioning. Yet, significant individual differences exist in this regard. Some older adults continue to retain most cognitive abilities throughout their lifetime. Others experience declines in cognitive and functional capacity that range from mild decrements in certain cognitive functions over time to severe dementia among those with neurodegenerative diseases. Even among relatively healthy "successful agers," certain cognitive functions are reduced from earlier levels. This is particularly true for cognitive functions that are dependent on cognitive processing speed and efficiency. Working memory and executive and attentional functions tend to be most vulnerable. Learning and memory functions are also usually reduced, although in the absence of neurodegenerative disease learning and retrieval efficiency rather than memory storage are affected. Other functions, such as visual perception, language, semantics, and knowledge, are often well preserved. Structural, functional, and physiologic/metabolic brain changes correspond with age-associated cognitive decline. Physiologic and metabolic mechanisms, such as oxidative stress and neuroinflammation, may contribute to these changes, along with the contribution of comorbidities that secondarily affect the brain of older adults. Cognitive frailty often corresponds with physical frailty, both affected by multiple exogenous and endogenous factors. Neuropsychologic assessment provides a way of measuring the cognitive and functional status of older adults, which is useful for monitoring changes that may be occurring. Neuroimaging is also useful for characterizing age-associated structural, functional, physiologic, and metabolic brain changes, including alterations in cerebral blood flow and metabolite concentrations. Some interventions that may enhance cognitive function, such as cognitive training, neuromodulation, and pharmacologic approaches, exist or are being developed. Yet, preventing, slowing, and reversing the adverse effects of cognitive aging remains a challenge.

Facing up to the global challenges of ageing

Longer human lives have led to a global burden of late-life disease. However, some older people experience little ill health, a trait that should be extended to the general population. Interventions into lifestyle, including increased exercise and reduction in food intake and obesity, can help to maintain healthspan. Altered gut microbiota, removal of senescent cells, blood factors obtained from young individuals and drugs can all improve late-life health in animals. Application to humans will require better biomarkers of disease risk and responses to interventions, closer alignment of work in animals and humans, and increased use of electronic health records, biobank resources and cohort studies.

Genetics: Healthy ageing, the genome and the environment

The sequenced genomes of individuals aged ≥ 80 years, who were highly educated, self referred volunteers and with no self reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect against disease might be enriched in this population.