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- Landén, Mikael, 1966, et al.
(author)
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Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
- 2021
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In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 5124-5139
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Journal article (peer-reviewed)abstract
- Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates. © 2020, The Author(s).
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| 2. |
- Franks, P. W., et al.
(author)
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Genomic variants at the PINK1 locus are associated with transcript abundance and plasma nonesterified fatty acid concentrations in European whites
- 2008
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In: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 22:9, s. 3135-3145
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Journal article (peer-reviewed)abstract
- The purpose of this study was to characterize associations between PINK1 genotypes, PINK1 transcript levels, and metabolic phenotypes in healthy adults and those with type 2 diabetes (T2D). We measured PINK1 skeletal muscle transcript levels and 8 independent PINK1 single nucleotide polymorphisms (SNPs) in a cohort of 208 Danish whites and in a cohort of 1701 British whites (SNPs and metabolic phenotypes only). Furthermore, we assessed the effects of PINK1 transcript ablation in primary adipocytes using RNA interference (RNAi). Six PINK1 SNPs were associated with PINK1 transcript levels (P < 0.04 to P < 0.0001). Obesity modified the association between PINK1 transcript levels and T2D risk (interaction P=0.005); transcript levels were inversely related with T2D in obese (n=105) [odds ratio (OR) per SD increase in expression levels=0.44; 95% confidence interval (CI): 0.23, 0.84; P=0.013] but not in nonobese (n=103) (OR=1.20; 95% CI: 0.82, 1.76; P=0.34) individuals. In the British cohort, several PINK1 SNPs were associated with plasma nonesterified fatty acid concentrations. Nominal genotype associations were also observed for fasting glucose, 2-h glucose, and maximal oxygen consumption, although these were not statistically significant after correcting for multiple testing. In primary adipocytes, Pink1 knockdown affected fatty acid binding protein 4 (Fabp4) expression, indicating that PINK1 may influence substrate metabolism. We demonstrate that PINK1 polymorphisms are associated with PINK1 transcript levels and measures of fatty acid metabolism in a concordant manner, whereas our RNAi data imply that PINK1 may indirectly influence lipid metabolism.
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