High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual’s polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40–69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55–85 years), Older Australian Twins Study (n = 539, 65–90 years) and Sydney Memory and Ageing Study (n = 925, 70–90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70–93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22–30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10–42) and its components (p < 2.30 × 10–8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity

High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10-42) and its components (p < 2.30 × 10-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Association of CSF biomarkers with MRI brain changes in Alzheimer's disease

Abstract The relation between cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and magnetic resonance imaging (MRI) measures is poorly understood in cognitively healthy individuals from the general population. Participants’ (n = 226) mean age was 70.9 years (SD = 0.4). CSF concentrations of amyloid beta (Aβ)1‐42, total tau (t‐tau), phosphorylated tau (p‐tau), neurogranin, and neurofilament light, and volumes of hippocampus, amygdala, total basal forebrain (TBF), and cortical thickness were measured. Linear associations between CSF biomarkers and MRI measures were investigated. In Aβ1‐42 positives, higher t‐tau and p‐tau were associated with smaller hippocampus (P = 0.001 and P = 0.003) and amygdala (P = 0.005 and P = 0.01). In Aβ1‐42 negatives, higher t‐tau, p‐tau, and neurogranin were associated with larger TBF volume (P = 0.001, P = 0.001, and P = 0.01). No associations were observed between the CSF biomarkers and an AD signature score of cortical thickness. AD‐specific biomarkers in cognitively healthy 70‐year‐olds may be related to TBF, hippocampus, and amygdala. Lack of association with cortical thickness might be due to early stage of disease

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease

Nat Commun

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease