Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Food preferences significantly influence dietary choices, yet understanding natural dietary patterns in populations remains limited. Here we identifiy four dietary subtypes by applying data-driven approaches to food-liking data from 181,990 UK Biobank participants: ‘starch-free or reduced-starch’ (subtype 1), ‘vegetarian’ (subtype 2), ‘high protein and low fiber’ (subtype 3) and ‘balanced’ (subtype 4). These subtypes varied in diverse brain health domains. The individuals with a balanced diet demonstrated better mental health and superior cognitive functions relative to other three subtypes. Compared with subtype 4, subtype 3 displayed lower gray matter volumes in regions such as the postcentral gyrus, while subtype 2 showed higher volumes in thalamus and precuneus. Genome-wide association analyses identified 16 genes different between subtype 3 and subtype 4, enriched in biological processes related to mental health and cognition. These findings provide new insights into naturally developed dietary patterns, highlighting the importance of a balanced diet for brain health.

Related collections

Most cited references 117

Record: found
Abstract: found
Article: not found

The Satisfaction With Life Scale.

Ed Diener, Robert A Emmons, Randy Larsen … (2010)

This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is Suited for use with different age groups, and other potential uses of the scale are discussed.

0 comments Cited 3173 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Second-generation PLINK: rising to the challenge of larger and richer datasets

Christopher Chang, Carson Chow, Laurent Tellier … (2015)

PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.

0 comments Cited 2835 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

The UK Biobank resource with deep phenotyping and genomic data

Clare Bycroft, Colin Freeman, Desislava Petkova … (2018)

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.