| 1. |
- Thompson, Paul M., et al.
(författare)
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The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
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Ingår i: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
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Tidskriftsartikel (refereegranskat)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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| 2. |
- Ried, Janina S., et al.
(författare)
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A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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| 3. |
- Yang, Jian, et al.
(författare)
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FTO genotype is associated with phenotypic variability of body mass index
- 2012
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 490:7419, s. 267-272
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Tidskriftsartikel (refereegranskat)abstract
- There is evidence across several species for genetic control of phenotypic variation of complex traits(1-4), such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using similar to 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)(5-7), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of similar to 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation(9,10). Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
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| 4. |
- Chatterjee, Pratishtha, et al.
(författare)
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Diagnostic and prognostic plasma biomarkers for preclinical Alzheimer's disease.
- 2022
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Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - : Wiley. - 1552-5279. ; 18:6, s. 1141-1154
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Tidskriftsartikel (refereegranskat)abstract
- This study involved a parallel comparison of the diagnostic and longitudinal monitoring potential of plasma glial fibrillary acidic protein (GFAP), total tau (t-tau), phosphorylated tau (p-tau181 and p-tau231), and neurofilament light (NFL) in preclinical Alzheimer's disease (AD).Plasma proteins were measured using Simoa assays in cognitively unimpaired older adults (CU), with either absence (Aβ-) or presence (Aβ+) of brain amyloidosis.Plasma GFAP, t-tau, p-tau181, and p-tau231 concentrations were higher in Aβ+ CU compared with Aβ- CU cross-sectionally. GFAP had the highest effect size and area under the curve (AUC) in differentiating between Aβ+ and Aβ- CU; however, no statistically significant differences were observed between the AUCs of GFAP, p-tau181, and p-tau231, but all were significantly higher than the AUC of NFL, and the AUC of GFAP was higher than the AUC of t-tau. The combination of a base model (BM), comprising the AD risk factors, age, sex, and apolipoprotein E gene (APOE) ε4 status with GFAP was observed to have a higher AUC (>90%) compared with the combination of BM with any of the other proteins investigated in the current study. Longitudinal analyses showed increased GFAP and p-tau181 in Aβ+ CU and increased NFL in Aβ- CU, over a 12-month duration. GFAP, p-tau181, p-tau231, and NFL showed significant correlations with cognition, whereas no significant correlations were observed with hippocampal volume.These findings highlight the diagnostic and longitudinal monitoring potential of GFAP and p-tau for preclinical AD.
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