Background: Mid-life hypertension is an established risk factor for cognitive impairment and dementia and related to greater brain atrophy and poorer cognitive performance. Previous studies often have small sample sizes from older populations that lack utilizing multiple measures to define hypertension such as blood pressure, self-report information, and medication use; furthermore, the impact of the duration of hypertension is less extensively studied. Objective: To investigate the relationship between hypertension defined using multiple measures and length of hypertension with brain measure and cognition. Methods: Using participants from the UK Biobank MRI visit with blood pressure measurements (n = 31,513), we examined the cross-sectional relationships between hypertension and duration of hypertension with brain volumes and cognitive tests using generalized linear models adjusted for confounding. Results: Compared with normotensives, hypertensive participants had smaller brain volumes, larger white matter hyperintensities (WMH), and poorer performance on cognitive tests. For total brain, total grey, and hippocampal volumes, those with greatest duration of hypertension had the smallest brain volumes and the largest WMH, ventricular cerebrospinal fluid volumes. For other subcortical and white matter microstructural regions, there was no clear relationship. There were no significant associations between duration of hypertension and cognitive tests. Conclusion: Our results show hypertension is associated with poorer brain and cognitive health however, the impact of duration since diagnosis warrants further investigation. This work adds further insights by using multiple measures defining hypertension and analysis on duration of hypertension which is a substantial advance on prior analyses—particularly those in UK Biobank which present otherwise similar analyses on smaller subsets.
BACKGROUND: Findings from randomized controlled trials have yielded conflicting results on the association between blood pressure (BP) and dementia traits. We tested the hypothesis that a causal relationship exists between systolic BP (SBP) and/or diastolic BP (DBP) and risk of Alzheimer's disease (AD). METHODS: We performed a generalized summary Mendelian randomization (GSMR) analysis using summary statistics of a genome-wide association study meta-analysis of 299,024 individuals of SBP or DBP as exposure variables against three different outcomes: 1) AD diagnosis (International Genomics of Alzheimer's Project), 2) maternal family history of AD (UK Biobank), and 3) paternal family history of AD (UK Biobank). Finally, a combined meta-analysis of 368,440 individuals that included these three summary statistics was used as final outcome. RESULTS: GSMR applied to the International Genomics of Alzheimer's Project dataset revealed a significant effect of high SBP lowering the risk of AD (b GSMR = 20.19, p = .04). GSMR applied to the maternal family history of AD UK Biobank dataset (SBP [b GSMR = 20.12, p = .02], DBP [b GSMR = 20.10, p = .05]) and to the paternal family history of AD UK Biobank dataset (SBP [b GSMR = 20.16, p = .02], DBP [b GSMR = 20.24, p = 7.4 3 10 24 ]) showed the same effect. A subsequent combined meta-analysis confirmed the overall significant effect for the other SBP analyses (b GSMR = 20.14, p = .03). The DBP analysis in the combined meta-analysis also confirmed a DBP effect on AD (b GSMR = 20.14, p = .03). CONCLUSIONS: A causal effect exists between high BP and a reduced late-life risk of AD. The results were obtained through careful consideration of confounding factors and the application of complementary MR methods on independent cohorts.
In the recent decades, the evolution of omics technologies has led to advances in all biological fields, creating a demand for effective storage, management and exchange of rapidly generated data and research discoveries. To address this need, the development of databases of experimental outputs has become a common part of scientific practice in order to serve as knowledge sources and data-sharing platforms, providing information about genes, transcripts, proteins or metabolites. In this review, we present omics databases available currently, with a special focus on their application in kidney research and possibly in clinical practice. Databases are divided into two categories: general databases with a broad information scope and kidney-specific databases distinctively concentrated on kidney pathologies. In research, databases can be used as a rich source of information about pathophysiological mechanisms and molecular targets. In the future, databases will support clinicians with their decisions, providing better and faster diagnoses and setting the direction towards more preventive, personalized medicine. We also provide a test case demonstrating the potential of biological databases in comparing multi-omics datasets and generating new hypotheses to answer a critical and common diagnostic problem in nephrology practice. In the future, employment of databases combined with data integration and data mining should provide powerful insights into unlocking the mysteries of kidney disease, leading to a potential impact on pharmacological intervention and therapeutic disease management.
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