| 1. |
- Landén, Mikael, 1966, et al.
(author)
-
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
- 2021
-
In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 5124-5139
-
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).
|
|
| 2. |
- van der Voort, L. H. M. Rouppe, et al.
(author)
-
High-resolution observations of the solar photosphere, chromosphere, and transition region : A database of coordinated IRIS and SST observations
- 2020
-
In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 641
-
Journal article (peer-reviewed)abstract
- NASA’s Interface Region Imaging Spectrograph (IRIS) provides high-resolution observations of the solar atmosphere through ultraviolet spectroscopy and imaging. Since the launch of IRIS in June 2013, we have conducted systematic observation campaigns in coordination with the Swedish 1 m Solar Telescope (SST) on La Palma. The SST provides complementary high-resolution observations of the photosphere and chromosphere. The SST observations include spectropolarimetric imaging in photospheric Fe I lines and spectrally resolved imaging in the chromospheric Ca II 8542 Å, Hα, and Ca II K lines. We present a database of co-aligned IRIS and SST datasets that is open for analysis to the scientific community. The database covers a variety of targets including active regions, sunspots, plages, the quiet Sun, and coronal holes.
|
|
| 3. |
- Franks, P. W., et al.
(author)
-
Genomic variants at the PINK1 locus are associated with transcript abundance and plasma nonesterified fatty acid concentrations in European whites
- 2008
-
In: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 22:9, s. 3135-3145
-
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.
|
|
| 4. |
- Timmons, James A., et al.
(author)
-
Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans
- 2010
-
In: Journal of applied physiology. - : American Physiological Society. - 8750-7587 .- 1522-1601. ; 108:6, s. 1487-1496
-
Journal article (peer-reviewed)abstract
- Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Akerstrom T, MacDougald OA, Jansson E, Greenhaff PL, Tarnopolsky MA, van Loon LJ, Pedersen BK, Sundberg CJ, Wahlestedt C, Britton SL, Bouchard C. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol 108: 1487-1496, 2010. First published February 4, 2010; doi:10.1152/japplphysiol.01295.2009.-A low maximal oxygen consumption ((V) over dotO(2max)) is a strong risk factor for premature mortality. Supervised endurance exercise training increases (V) over dotO(2max) with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample sizes. In the present study, we first use RNA expression profiling to produce a molecular classifier that predicts (V) over dotO(2max) training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous (V) over dotO(2max) response. Two independent preintervention RNA expression data sets were generated (n = 41 gene chips) from subjects that underwent supervised endurance training: one identified and the second blindly validated an RNA expression signature that predicted change in (V) over dotO(2max) (""predictor"" genes). The HERITAGE Family Study (n = 473) was used for genotyping. We discovered a 29-RNA signature that predicted (V) over dotO(2max) training response on a continuous scale; these genes contained similar to 6 new single-nucleotide polymorphisms associated with gains in (V) over dotO(2max) in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., ""reciprocal"" RNA validation of a quantitative trait locus genotype), enhancing the performance of the 29-RNA-based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in (V) over dotO(2max), corresponding to similar to 50% of the estimated genetic variance for (V) over dotO(2max). In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. (V) over dotO(2max) responses to endurance training can be predicted by measuring a similar to 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.
|
|
| 5. |
- Lang, Justin J., et al.
(author)
-
Top 10 International Priorities for Physical Fitness Research and Surveillance Among Children and Adolescents : A Twin-Panel Delphi Study
- 2023
-
In: Sports Medicine. - New Zealand : Adis International Ltd.. - 0112-1642 .- 1179-2035. ; 53:2, s. 549-564
-
Journal article (peer-reviewed)abstract
- Background The measurement of physical fitness has a history that dates back nearly 200 years. Recently, there has been an increase in international research and surveillance on physical fitness creating a need for setting international priorities that could help guide future efforts. Objective This study aimed to produce a list of the top 10 international priorities for research and surveillance on physical fitness among children and adolescents. Methods Using a twin-panel Delphi method, two independent panels consisting of 46 international experts were identified (panel 1 = 28, panel 2 = 18). The panel participants were asked to list up to five priorities for research or surveillance (round 1), and then rated the items from their own panel on a 5-point Likert scale of importance (round 2). In round 3, experts were asked to rate the priorities identified by the other panel. Results There was strong between-panel agreement (panel 1: r(s) = 0.76, p < 0.01; panel 2: r(s) = 0.77, p < 0.01) in the priorities identified. The list of the final top 10 priorities included (i) "conduct longitudinal studies to assess changes in fitness and associations with health". This was followed by (ii) "use fitness surveillance to inform decision making", and (iii) "implement regular and consistent international/national fitness surveys using common measures". Conclusions The priorities identified in this study provide guidance for future international collaborations and research efforts on the physical fitness of children and adolescents over the next decade and beyond.
|
|
| 6. |
- Scheele, Camilla, et al.
(author)
-
Altered regulation of the PINK1 locus: a link between Type 2 diabetes and neurodegeneration?
- 2007
-
In: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 21:13, s. 3653-3665
-
Journal article (peer-reviewed)abstract
- Mutations in PINK1 cause the mitochondrial-related neurodegenerative disease Parkinson’s. Here we investigate whether obesity, type 2 diabetes, or inactivity alters transcription from the PINK1 locus. We utilized a cDNA-array and quantitative real-time PCR for gene expression analysis of muscle from healthy volunteers following physical inactivity, and muscle and adipose tissue from nonobese or obese subjects with normal glucose tolerance or type 2 diabetes. Functional studies of PINK1 were performed utilizing RNA interference in cell culture models. Following inactivity, the PINK1 locus had an opposing regulation pattern (PINK1 was down-regulated while natural antisense PINK1 was up-regulated). In type 2 diabetes skeletal muscle, all transcripts from the PINK1 locus were suppressed and gene expression correlated with diabetes status. RNA interference of PINK1 in human neuronal cell lines impaired basal glucose uptake. In adipose tissue, mitochondrial gene expression correlated with PINK1 expression although remained unaltered following siRNA knockdown of Pink1 in primary cultures of brown preadipocytes. In conclusion, regulation of the PINK1 locus, previously linked to neurodegenerative disease, is altered in obesity, type 2 diabetes and inactivity, while the combination of RNAi experiments and clinical data suggests a role for PINK1 in cell energetics rather than in mitochondrial biogenesis.
|
|
| 7. |
- Sood, Sanjana, et al.
(author)
-
A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status
- 2015
-
In: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 16
-
Journal article (peer-reviewed)abstract
- Background: Diagnostics of the human ageing process may help predict future healthcare needs or guide preventative measures for tackling diseases of older age. We take a transcriptomics approach to build the first reproducible multi-tissue RNA expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health. Results: One hundred and fifty probe-sets form an accurate classifier of young versus older muscle tissue and this healthy ageing RNA classifier performed consistently in independent cohorts of human muscle, skin and brain tissue (n = 594, AUC = 0.83-0.96) and thus represents a biomarker for biological age. Using the Uppsala Longitudinal Study of Adult Men birth-cohort (n = 108) we demonstrate that the RNA classifier is insensitive to confounding lifestyle biomarkers, while greater gene score at age 70 years is independently associated with better renal function at age 82 years and longevity. The gene score is 'up-regulated' in healthy human hippocampus with age, and when applied to blood RNA profiles from two large independent age-matched dementia case-control data sets (n = 717) the healthy controls have significantly greater gene scores than those with cognitive impairment. Alone, or when combined with our previously described prototype Alzheimer disease (AD) RNA 'disease signature', the healthy ageing RNA classifier is diagnostic for AD. Conclusions: We identify a novel and statistically robust multi-tissue RNA signature of human healthy ageing that can act as a diagnostic of future health, using only a peripheral blood sample. This RNA signature has great potential to assist research aimed at finding treatments for and/or management of AD and other ageing-related conditions.
|
|
| 8. |
- Keller, Pernille, et al.
(author)
-
Gene-chip studies of adipogenesis-regulated microRNAs in mouse primary adipocytes and human obesity
- 2011
-
In: BMC Endocrine Disorders. - : Springer Science and Business Media LLC. - 1472-6823. ; 11, s. 7-
-
Journal article (peer-reviewed)abstract
- BACKGROUND: Adipose tissue abundance relies partly on the factors that regulate adipogenesis, i.e. proliferation and differentiation of adipocytes. While components of the transcriptional program that initiates adipogenesis is well-known, the importance of microRNAs in adipogenesis is less well studied. We thus set out to investigate whether miRNAs would be actively modulated during adipogenesis and obesity.METHODS: Several models exist to study adipogenesis in vitro, of which the cell line 3T3-L1 is the most well known, albeit not the most physiologically appropriate. Thus, as an alternative, we produced EXIQON microarray of brown and white primary murine adipocytes (prior to and following differentiation) to yield global profiles of miRNAs.RESULTS: We found 65 miRNAs regulated during in vitro adipogenesis in primary adipocytes. We evaluated the similarity of our responses to those found in non-primary cell models, through literature data-mining. When comparing primary adipocyte profiles, with those of cell lines reported in the literature, we found a high degree of difference in 'adipogenesis' regulated miRNAs suggesting that the model systems may not be accurately representing adipogenesis. The expression of 10 adipogenesis-regulated miRNAs were studied using real-time qPCR and then we selected 5 miRNAs, that showed robust expression, were profiled in subcutaneous adipose tissue obtained from 20 humans with a range of body mass indices (BMI, range = 21-48, and all samples have U133+2 Affymetrix profiles provided). Of the miRNAs tested, mir-21 was robustly expressed in human adipose tissue and positively correlated with BMI (R2 = 0.49, p < 0.001).CONCLUSION: In conclusion, we provide a preliminary analysis of miRNAs associated with primary cell in vitro adipogenesis and demonstrate that the inflammation-associated miRNA, mir-21 is up-regulated in subcutaneous adipose tissue in human obesity. Further, we provide a novel transcriptomics database of EXIQON and Affymetrix adipocyte profiles to facilitate data mining.
|
|
| 9. |
|
|
| 10. |
|
|
