Ville-Petteri Mäkinen

Long-term Leisure-time Physical Activity and Serum Metabolome

Background— Long-term physical inactivity seems to cause many health problems. We studied whether persistent physical activity compared with inactivity has a global effect on serum metabolome toward reduced cardiometabolic disease risk. Methods and Results— Sixteen same-sex twin pairs (mean age, 60 years) were selected from a cohort of twin pairs on the basis of their >30-year discordance for physical activity. Persistently (≥5 years) active and inactive groups in 3 population-based cohorts (mean ages, 31–52 years) were also studied (1037 age- and sex-matched pairs). Serum metabolome was quantified by nuclear magnetic resonance spectroscopy. We used permutation analysis to estimate the significance of the multivariate effect combined across all metabolic measures; univariate effects were estimated by paired testing in twins and in matched pairs in the cohorts, and by meta-analysis over all substudies. Persistent physical activity was associated with the multivariate metabolic profile in the twins (P=0.003), and a similar pattern was observed in all 3 population cohorts with differing mean ages. Isoleucine, &agr;1-acid glycoprotein, and glucose were lower in the physically active than in the inactive individuals (P<0.001 in meta-analysis); serum fatty acid composition was shifted toward a less saturated profile; and lipoprotein subclasses were shifted toward lower very-low-density lipoprotein (P<0.001) and higher large and very large high-density lipoprotein (P<0.001) particle concentrations. The findings persisted after adjustment for body mass index. Conclusions— The numerous differences found between persistently physically active and inactive individuals in the circulating metabolome together indicate better metabolic health in the physically active than in inactive individuals.

Systems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases

The metabolically connected triad of obesity, diabetes, and cardiovascular diseases is a major public health threat, and is expected to worsen due to the global shift toward energy-rich and sedentary living. Despite decades of intense research, a large part of the molecular pathogenesis behind complex metabolic diseases remains unknown. Recent advances in genetics, epigenomics, transcriptomics, proteomics and metabolomics enable us to obtain large-scale snapshots of the etiological processes in multiple disease-related cells, tissues and organs. These datasets provide us with an opportunity to go beyond conventional reductionist approaches and to pinpoint the specific perturbations in critical biological processes. In this review, we summarize systems biology methodologies such as functional genomics, causality inference, data-driven biological network construction, and higher-level integrative analyses that can produce novel mechanistic insights, identify disease biomarkers, and uncover potential therapeutic targets from a combination of omics datasets. Importantly, we also demonstrate the power of these approaches by application examples in obesity, diabetes, and cardiovascular diseases.

Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease

Objective— Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Approaches and Results— Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-&bgr;/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. Conclusions— These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.

Chromosome 2q31.1 Associates with ESRD in Women with Type 1 Diabetes

Sex and genetic variation influence the risk of developing diabetic nephropathy and ESRD in patients with type 1 diabetes. We performed a genome-wide association study in a cohort of 3652 patients from the Finnish Diabetic Nephropathy (FinnDiane) Study with type 1 diabetes to determine whether sex-specific genetic risk factors for ESRD exist. A common variant, rs4972593 on chromosome 2q31.1, was associated with ESRD in women (P<5×10(-8)) but not in men (P=0.77). This association was replicated in the meta-analysis of three independent type 1 diabetes cohorts (P=0.02) and remained significant for women (P<5×10(-8); odds ratio, 1.81 [95% confidence interval, 1.47 to 2.24]) upon combined meta-analysis of the discovery and replication cohorts. rs4972593 is located between the genes that code for the Sp3 transcription factor, which interacts directly with estrogen receptor α and regulates the expression of genes linked to glomerular function and the pathogenesis of nephropathy, and the CDCA7 transcription factor, which regulates cell proliferation. Further examination revealed potential transcription factor-binding sites within rs4972593 and predicted eight estrogen-responsive elements within 5 kb of this locus. Moreover, we found sex-specific differences in the glomerular expression levels of SP3 (P=0.004). Overall, these results suggest that rs4972593 is a sex-specific genetic variant associated with ESRD in patients with type 1 diabetes and may underlie the sex-specific protection against ESRD.

Triglyceride-cholesterol imbalance across lipoprotein subclasses predicts diabetic kidney disease and mortality in type 1 diabetes: the FinnDiane Study

Circulating cholesterol (C) and triglyceride (TG) levels are associated with vascular injury in type 1 diabetes (T1DM). Lipoproteins are responsible for transporting lipids, and alterations in their subclass distributions may partly explain the increased mortality in individuals with T1DM.

Associations and interactions between lipid profiles, retinopathy and nephropathy in patients with type 1 diabetes: the FinnDiane Study

The aim of this study was to investigate the associations between lipid profiles and retinopathy in the large nationwide FinnDiane Study and to examine interactions and correlations between retinopathy, nephropathy and lipid variables.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration

BackgroundHuman diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development.ResultsTo make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server (http://mergeomics.research.idre.ucla.edu/). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use.ConclusionsOur Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

Patients with type 1 diabetes show signs of vascular dysfunction in response to multiple high-fat meals

BackgroundA high-fat diet promotes postprandial systemic inflammation and metabolic endotoxemia. We investigated the effects of three consecutive high-fat meals on endotoxemia, inflammation, vascular function, and postprandial lipid metabolism in patients with type 1 diabetes.MethodsNon-diabetic controls (n = 34) and patients with type 1 diabetes (n = 37) were given three high-caloric, fat-containing meals during one day. Blood samples were drawn at fasting (8:00) and every two hours thereafter until 18:00. Applanation tonometry was used to assess changes in the augmentation index during the investigation day.ResultsThree consecutive high-fat meals had only a modest effect on serum LPS-activity levels and inflammatory markers throughout the day in both groups. Of note, patients with type 1 diabetes were unable to decrease the augmentation index in response to the high-fat meals. The most profound effects of the consecutive fat loads were seen in chylomicron and HDL-metabolism. The triglyceride-rich lipoprotein remnant marker, apoB-48, was elevated in patients compared to controls both at fasting (p = 0.014) and postprandially (p = 0.035). The activities of the HDL-associated enzymes PLTP (p < 0.001), and CETP (p = 0.007) were higher and paraoxonase (PON-1) activity, an anti-oxidative enzyme bound to HDL, decreased in patients with type 1 diabetes (p = 0.027).ConclusionsIn response to high-fat meals, early signs of vascular dysfunction alongside accumulation of chylomicron remnants, higher augmentation index, and decreased PON-1 activity were observed in patients with type 1 diabetes. The high-fat meals had no significant impact on postprandial LPS-activity in non-diabetic subjects or patients with type 1 diabetes suggesting that metabolic endotoxemia may be more central in patients with chronic metabolic disturbances such as obesity, type 2 diabetes, or diabetic kidney disease.

Metabolic Phenotyping of Diabetic Nephropathy

Diabetic nephropathy is the most serious complication of type 1 diabetes. There is no treatment to protect the kidneys from poorly controlled diabetes, and therefore prevention of the initial metabolic insults is currently the only effective approach to reducing the high mortality related to diabetic nephropathy. Metabolic phenotyping brings us one step closer to understanding the unique set of regulatory perturbations that predispose to kidney injury and paves the way for multiparametric risk assessment.

Metabolomics of aging requires large-scale longitudinal studies with replication

Aging is a complex biological process with remarkable individual variation and manifests also as changes in systemic metabolism. In a recent paper in PNAS, Chaleckis et al. (1) studied a set of blood metabolites in old and young individuals. The work was thorough in the methodological aspects regarding the mass spectrometry of circulating molecules in plasma, red blood cells, and whole blood. However, we find it alarming that the results and interpretations on the suggested age-related metabolic differences were not properly put into epidemiological context. We therefore draw attention to four key issues: ( i ) metabolic heterogeneity of … [↵][1]1To whom correspondence should be addressed. Email: ville-petteri.makinen{at}sahmri.com. [1]: #xref-corresp-1-1