Genetic susceptibility to cardiovascular disease and risk of dementia

NHANES 2011-2014 Reveals Decreased Cognitive Performance in U.S. Older Adults with Metabolic Syndrome Combinations

A relationship between metabolic syndrome and cognitive impairment has been evidenced across research; however, conflicting results have been observed. A cross-sectional study was conducted on 3179 adults older than 60 from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) to analyze the relationship between metabolic syndrome and cognitive impairment. In our results, we found that adults with abdominal obesity, high triglycerides, and low HDL cholesterol had 4.39 fewer points in the CERAD immediate recall test than adults without any metabolic syndrome factors [Beta = -4.39, SE = 1.32, 17.75 (1.36) vs. 22.14 (0.76)]. In addition, people with this metabolic syndrome combination exhibited 2.39 fewer points in the CERAD delayed recall test than those without metabolic syndrome criteria [Beta = -2.39, SE = 0.46, 4.32 (0.49) vs. 6.71 (0.30)]. It was also found that persons with high blood pressure, hyperglycemia, and low HDL-cholesterol levels reached 4.11 points less in the animal fluency test than people with no factors [Beta = -4.11, SE = 1.55, 12.67 (2.12) vs. 16.79 (1.35)]. These findings suggest that specific metabolic syndrome combinations are essential predictors of cognitive impairment. In this study, metabolic syndrome combinations that included obesity, fasting hyperglycemia, high triglycerides, and low HDL-cholesterol were among the most frequent criteria observed.

Cardiometabolic diseases, polygenic risk score, APOE genotype, and risk of incident dementia: A population-based prospective cohort study

Objective We aimed to prospective investigate the association between cardiometabolic diseases (CMDs) with dementia, and to examine whether genetic factors and CMDs jointly contribute to the incidence of dementia. Methods We used data from the UK biobank of 204,646 adults aged 37-73 free of dementia at baseline. Genetic risk for dementia including APOE ε4 status and polygenic risk score (PRS) categorized as low, intermediate, and high. CMDs including ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D) were confirmed by touchscreen questionnaires, medical examinations, and hospital inpatient records. Results Over the follow-up (median: 12.5 years), 5,750 participants developed dementia. The HRs (95% CI) of those with APOE ε4 carriers and high PRS were 3.16 (3.00-3.33) and 1.50 (1.41-1.60), respectively. The risk of dementia was 70% higher among those with CMDs (HR: 1.70; 95% CI: 1.60-1.82). In joint effect analyses, compared to no CMDs and APOE ε4 non-carriers, the HRs (95% CIs) of dementia were 3.53 (3.31-3.76)/2.06 (1.89-2.23) in participants with only APOE ε4 carriers and CMDs, and 5.06 (4.64-5.53) for those with APOE ε4 carriers plus CMDs. Compared to no CMDs and low PRS, the HRs (95% CIs) of dementia were 1.29 (1.19-1.40)/1.60 (1.48-1.73) in participants with only intermediate and high PRS, and 2.00 (1.79-2.23)/2.63 (2.38-2.92) for those with intermediate, and high PRS plus CMDs. Moreover, there were significant additive and multiplication interactions between CMDs and APOE ε4 carriers of dementia, but only multiplication interaction was observed for PRS. Conclusions CMDs were associated with higher risk of dementia regardless of genetic risk for dementia.

Cardiometabolic multimorbidity and incident dementia: the Swedish twin registry

AIMS

Cardiometabolic diseases (CMDs), including diabetes, heart disease, and stroke, are established risk factors for dementia, but their combined impact has been investigated only recently. This study aimed to examine the association between mid- and late-life cardiometabolic multimorbidity and dementia and explore the role of genetic background in this association.

METHODS AND RESULTS

Within the Swedish Twin Registry, 17 913 dementia-free individuals aged ≥60 were followed for 18 years. CMDs [including age of onset in mid (60) or late (≥60) life] and dementia were ascertained from medical records. Cardiometabolic multimorbidity was defined as having ≥2 CMDs. Cox regression was used to estimate the CMD-dementia association in (i) a classical cohort study design and (ii) a co-twin study design involving 356 monozygotic and dizygotic pairs. By comparing the strength of the association in the two designs, the contribution of genetic background was estimated. At baseline, 3,312 (18.5%) participants had 1 CMD and 839 (4.7%) had ≥2 CMDs. Over the follow-up period, 3,020 participants developed dementia. In the classic cohort design, the hazard ratio (95% confidence interval) of dementia was 1.42 (1.27-1.58) for 1 CMD and 2.10 (1.73-2.57) for ≥2 CMDs. Dementia risk was stronger with mid-life as opposed to late-life CMDs. In the co-twin design, the CMD-dementia association was attenuated among monozygotic [0.99 (0.50-1.98)] but not dizygotic [1.55 (1.15-2.09)] twins, suggesting that the association was in part due to genetic factors common to both CMDs and dementia.

CONCLUSION

Cardiometabolic multimorbidity, particularly in mid-life, is associated with an increased risk of dementia. Genetic background may underpin this association.

Impact of polygenic risk for coronary artery disease and cardiovascular medication burden on cognitive impairment in psychotic disorders

BACKGROUND

Cognitive impairment is a core deficit across psychotic disorders, the causes and therapeutics of which remain unclear. Epidemiological observations have suggested associations between cognitive dysfunction in psychotic disorders and cardiovascular risk factors, but an underlying etiology has not been established.

METHODS

Neuropsychological performance using the Brief Assessment of Cognition in Schizophrenia (BACS) was assessed in 616 individuals of European ancestry (403 psychosis, 213 controls). Polygenic risk scores for coronary artery disease (PRSCAD) were quantified for each participant across 13 p-value thresholds (PT 0.5-5e-8). Cardiovascular and psychotropic medications were categorized for association analyses. Each PRSCAD was examined in relation to the BACS and the optimized PT was confirmed with five-fold cross-validation and independent validation. Functional enrichment analyses were used to identify biological mechanisms linked to PRSCAD-cognition associations. Multiple regression analyses examined PRSCAD under the optimal PT and medication burden in relation to the BACS composite and subtest scores.

RESULTS

Higher PRSCAD was associated with lower BACS composite scores (p = 0.001) in the psychosis group, primarily driven by the Verbal Memory subtest (p < 0.001). Genes linked to multiple nervous system related processes and pathways were significantly enriched in PRSCAD. After controlling for PRSCAD, a greater number of cardiovascular medications was also correlated with worse BACS performance in patients with psychotic disorders (p = 0.029).

CONCLUSIONS

Higher PRSCAD and taking more cardiovascular medications were both significantly associated with cognitive impairment in psychosis. These findings indicate that cardiovascular factors may increase the risk for cognitive dysfunction and related functional outcomes among individuals with psychotic disorders.

Obstructive Sleep Apnea and Cognitive Decline: A Review of Potential Vulnerability and Protective Factors

Around 40% of dementia risk is attributable to modifiable risk factors such as physical inactivity, hypertension, diabetes and obesity. Recently, sleep disorders, including obstructive sleep apnea (OSA), have also been considered among these factors. However, despite several epidemiological studies investigating the link between OSA and cognitive decline, there is still no consensus on whether OSA increases the risk of dementia or not. Part of the heterogeneity observed in previous studies might be related to some individual characteristics that modulate the association between OSA and cognitive decline. In this narrative review, we present these individual characteristics, namely, age, sex, menopause, obesity, diabetes mellitus, hypertension, cardiovascular diseases, smoking, excessive alcohol consumption, depression, air pollution, Apolipoprotein E ε4 allele, physical activity, and cognitive reserve. To date, large cohort studies of OSA and cognitive decline tended to statistically control for the effects of these variables, but whether they interact with OSA to predict cognitive decline remains to be elucidated. Being able to better predict who is at risk of cognitive decline when they have OSA would improve clinical management and treatment decisions, particularly when patients present relatively mild OSA.

Transcriptomic Heterogeneity of Alzheimer's Disease Associated with Lipid Genetic Risk

Alzheimer's disease (AD) is a multifactorial disease that affects more than 5 million Americans. Multiple pathways might be involved in the AD pathogenesis. The implication of lipid genetic susceptibility on brain gene expression is yet to be investigated. The current study included 192 brain samples from AD patients who were enrolled in the ROSMAP study. The samples were genotyped and imputed to the HRC Reference Panel. Lipid polygenetic risk score was constructed from the weighted sum of genetic variants associated with low-density lipoprotein cholesterol (LDL-C). The gene expression was profiled by RNA sequencing, and the  association of gene expression with lipid polygenetic risk scores was tested by linear regression models adjusted for age, sex and APOE e4 alleles. Three genes were found to associate with lipid polygenetic risk scores, including HMCN2 (P = 3.6 × 10-7), PDLIM5 (P = 1.2 × 10-6), and FHL5 (P = 2.0 × 10-6). Network analysis revealed multiple related pathways, including dopaminergic synapse (P = 4.5 × 10-5), circadian entrainment (P = 1.1 × 10-4), and cholinergic synapse (P = 2.3 × 10-4). Our study underscores the importance of lipid regulation and metabolism to AD heterogeneity.

Predictors of Heterogeneity in Cognitive Function: APOE-e4, Sex, Education, Depression, and Vascular Risk

OBJECTIVE

Mild cognitive impairment and dementia are clinically heterogeneous disorders influenced by diverse risk factors. Improved characterization of the effect of multiple risk factors influence on specific cognitive functions may improve understanding of mechanisms in early cognitive change and lead to more effective interventions.

METHODS

Structural equation modeling (SEM) simultaneously examined the effects of modifiable (education, depression, and metabolic/vascular risk) and nonmodifiable risk factors (age, sex, and apolipoprotein E-ɛ4 allele [APOE-e4] status) on specific cognitive domains in 461 cognitively normal older adults.

RESULTS

The hypothesized model(s) provided an adequate fit for the data. Sex differences in cognition, depression, and vascular risk were found. On average, men were higher in vascular risk with generally lower cognitive performance than women; women were more likely to have depression. APOE-e4 associated with depression but not age, sex, or metabolic/vascular risk. Depression associated with lower executive attention, memory, and language performance, whereas metabolic/vascular risk associated with lower executive attention, memory, and working memory. Older age and lower education are associated with worse performance across the cognitive domains. The combined risk factors accounted for 16%-47% of the variance in the cognitive domains.

CONCLUSIONS

Results highlight the combined effect of risk factors on cognitive function. Future research is needed to determine whether the multifactorial risk effects on cognition vary by sex. Precision medicine approaches that integrate neuropsychological services may improve diagnostic accuracy and earlier identification of those at risk of cognitive decline.

Polygenic risk and pleiotropy in neurodegenerative diseases

In this paper we explore the phenomenon of pleiotropy in neurodegenerative diseases, focusing on Alzheimer's disease (AD). We summarize the various techniques developed to investigate pleiotropy among traits, elaborating in the polygenic risk scores (PRS) analysis. PRS was designed to assess a cumulative effect of a large number of SNPs for association with a disease and, later for disease risk prediction. Since genetic predictions rely on heritability, we discuss SNP-based heritability from genome-wide association studies and its contribution to the prediction accuracy of PRS. We review work examining pleiotropy in neurodegenerative diseases and related phenotypes and biomarkers. We conclude that the exploitation of pleiotropy may aid in the identification of novel genes and provide further insights in the disease mechanisms, and along with PRS analysis, may be advantageous for precision medicine.

Shared genetic architecture between metabolic traits and Alzheimer's disease: a large-scale genome-wide cross-trait analysis

A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer's disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P = 6.78 × 10^- 22), LDL (P = 1.74 × 10^- 253) and HDL (P = 7.94 × 10^- 18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (P_meta < 1.6 × 10^- 8, single trait P < 0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.

Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease

Cardiovascular (CV)- and lifestyle-associated risk factors (RFs) are increasingly recognized as important for Alzheimer's disease (AD) pathogenesis. Beyond the ε4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV-associated genes also increase risk for AD. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV-associated RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), triglycerides (TG), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TG, TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 90 SNPs on 19 different chromosomes that were jointly associated with AD and CV-associated outcomes. In meta-analyses across three independent cohorts, we found four novel loci within MBLAC1 (chromosome 7, meta-p = 1.44 × 10^-9), MINK1 (chromosome 17, meta-p = 1.98 × 10^-7) and two chromosome 11 SNPs within the MTCH2/SPI1 region (closest gene = DDB2, meta-p = 7.01 × 10^-7 and closest gene = MYBPC3, meta-p = 5.62 × 10^-8). In a large 'AD-by-proxy' cohort from the UK Biobank, we replicated three of the four novel AD/CV pleiotropic SNPs, namely variants within MINK1, MBLAC1, and DDB2. Expression of MBLAC1, SPI1, MINK1 and DDB2 was differentially altered within postmortem AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid-associated RFs. We pinpoint a subset of cardiovascular-associated genes that strongly increase the risk for AD. Our collective findings support a disease model in which cardiovascular biology is integral to the development of clinical AD in a subset of individuals.

Identification of 12 genetic loci associated with human healthspan

Aging populations face diminishing quality of life due to increased disease and morbidity. These challenges call for longevity research to focus on understanding the pathways controlling healthspan. We use the data from the UK Biobank (UKB) cohort and observe that the risks of major chronic diseases increased exponentially and double every eight years, i.e., at a rate compatible with the Gompertz mortality law. Assuming that aging drives the acceleration in morbidity rates, we build a risk model to predict the age at the end of healthspan depending on age, gender, and genetic background. Using the sub-population of 300,447 British individuals as a discovery cohort, we identify 12 loci associated with healthspan at the whole-genome significance level. We find strong genetic correlations between healthspan and all-cause mortality, life-history, and lifestyle traits. We thereby conclude that the healthspan offers a promising new way to interrogate the genetics of human longevity.