Multi-omic signature of body weight change: results from a population-based cohort study

BACKGROUND: Excess body weight is a major risk factor for cardiometabolic diseases. The complex molecular mechanisms of body weight change-induced metabolic perturbations are not fully understood. Specifically, in-depth molecular characterization of long-term body weight change in the general population is lacking. Here, we pursued a multi-omic approach to comprehensively study metabolic consequences of body weight change during a seven-year follow-up in a large prospective study. METHODS: We used data from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort. At follow-up (F4), two-platform serum metabolomics and whole blood gene expression measurements were obtained for 1,631 and 689 participants, respectively. Using weighted correlation network analysis, omics data were clustered into modules of closely connected molecules, followed by the formation of a partial correlation network from the modules. Association of the omics modules with previous annual percentage weight change was then determined using linear models. In addition, we performed pathway enrichment analyses, stability analyses, and assessed the relation of the omics modules with clinical traits. RESULTS: Four metabolite and two gene expression modules were significantly and stably associated with body weight change (P-values ranging from 1.9 × 10−4 to 1.2 × 10−24). The four metabolite modules covered major branches of metabolism, with VLDL, LDL and large HDL subclasses, triglycerides, branched-chain amino acids and markers of energy metabolism among the main representative molecules. One gene expression module suggests a role of weight change in red blood cell development. The other gene expression module largely overlaps with the lipid-leukocyte (LL) module previously reported to interact with serum metabolites, for which we identify additional co-expressed genes. The omics modules were interrelated and showed cross-sectional associations with clinical traits. Moreover, weight gain and weight loss showed largely opposing associations with the omics modules. CONCLUSIONS: Long-term weight change in the general population globally associates with serum metabolite concentrations. An integrated metabolomics and transcriptomics approach improved the understanding of molecular mechanisms underlying the association of weight gain with changes in lipid and amino acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function

Blocking sense-strand activity improves potency, safety and specificity of anti-hepatitis B virus short hairpin RNA.

Hepatitis B virus (HBV) is a promising target for therapies based on RNA interference (RNAi) since it replicates via RNA transcripts that are vulnerable to RNAi silencing. Clinical translation of RNAi technology, however, requires improvements in potency, specificity and safety. To this end, we systematically compared different strategies to express anti-HBV short hairpin RNA (shRNA) in a pre-clinical immunocompetent hepatitis B mouse model. Using recombinant Adeno-associated virus (AAV) 8 vectors for delivery, we either (i) embedded the shRNA in an artificial mi(cro)RNA under a liver-specific promoter; (ii) co-expressed Argonaute-2, a rate-limiting cellular factor whose saturation with excess RNAi triggers can be toxic; or (iii) co-delivered a decoy ("TuD") directed against the shRNA sense strand to curb off-target gene regulation. Remarkably, all three strategies minimised adverse side effects as compared to a conventional shRNA vector that caused weight loss, liver damage and dysregulation of > 100 hepatic genes. Importantly, the novel AAV8 vector co-expressing anti-HBV shRNA and TuD outperformed all other strategies regarding efficiency and persistence of HBV knock-down, thus showing substantial promise for clinical translation

Display of results at the individual diagnosis level “ABCA3 transporter deficiency, two mutations/Controls-healthy” (panel A) and B)) and “Controls-bronchitis/Controls-healthy” (panel C) and panel D)).

<p>A) and C) Phosphatidylcholine and B) and D) Phosphatidylglycerol species of the children with ABCA3 transporter deficiency due to two disease causing mutations (n = 5) or controls-bronchitis (n = 10) in relation to that of the control children (n = 11). Mean values of each group were taken for calculation of the ratio. A ratio below 1 indicates lower values in the children with ABCA3 transporter deficiency, i.e. lack of transport of such species into the alveolar space; a ratio above 1 indicates higher values in the children with ABCA3 transporter deficiency, i.e. accumulation of such species in the alveolar space.</p

Display of results at the individual diagnosis level for the disease category “ILD-related to the alveolar surfactant region”.

<p>Lipid class composition (graph A) on left side) and phosphatidylcholine species composition (graph B) on right side) are indicated as means for each diagnosis. The number of subjects is detailed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117985#pone.0117985.t001" target="_blank">Table 1</a>. The numbers above the columns indicate the mean phospholipid concentrations (μmol/l). No statistical comparisons were done; the graphical display should allow a rapid identification of deviations from the controls. The other species are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117985#pone.0117985.s004" target="_blank">S4 Fig</a>. Only lipid species present at an abundance of > 0.5% are displayed.</p

A) Phospholipid classes of the control groups (healthy (n = 11), left column of pair; bronchitis (n = 10), right column of pair).

<p>Lipid class composition is expressed as % of the analyzed displayed lipid classes (left graph). B) Phosphatidylcholine species composition is expressed as % phosphatidylcholine (right graph). The species of the other phospholipid classes are displayed in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117985#pone.0117985.s002" target="_blank">S2 Fig</a>. Data are means. Species present at an abundance of < 0.5% were not displayed.</p

Display of results at the disease category level.

<p>A) Phosphatidylcholine, the major surfactant phospholipid class and B) its species dipalmitoylphosphatidylcholine (PC 32:0) are given as individual results of all patients included in the study according the disease category they belong to. The statistical comparisons were done by ANOVA and Dunn’s post hoc test; all significant results are displayed in each figure. To take multiple comparisons into consideration, an overall cut-off level of P<0.0182 was calculated. For A) 1-way ANOVA gave a P = 0.0020, for B) P < 0.0038; the significant results of Dunn’s post hoc tests are indicated as following: ____ = P < 0.05, _ _ _ = P < 0.01, and …. = P < 0.001. The species of the other phosphatidylcholines, the other phospholipid classes and their species composition are displayed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117985#pone.0117985.s003" target="_blank">S3 Fig</a>. Horizontal bar indicates median.</p

Subjects included into the study, their allocation to pulmonary disease categories and subcategories, subjects excluded and final number of subjects.

<p>Subjects included into the study, their allocation to pulmonary disease categories and subcategories, subjects excluded and final number of subjects.</p

Calculation and expression of the results of the lipid analysis.

<p>All analyzed lipids are the sum of all analyzed phospholipid classes, cholesteryl ester and free cholesterol (all expressed as nmol/ml). Phospholipid classes are expressed as % of all analyzed phospholipids and the species as percentage of that phospholipid class. In the body of the manuscript mainly the results of all lipid classes and the composition of one of its classes, i.e. phosphatidylcholine, are indicated. Composition of the other classes are presented in the supplemental materials. For overview see also panel A in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117985#pone.0117985.s001" target="_blank">S1 Fig</a>.</p