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Sökning: WFRF:(Lamichhane Santosh)

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1.
  • Lozano, Rafael, et al. (författare)
  • Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
  • 2018
  • Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 392:10159, s. 2091-2138
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
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2.
  • Alves, Marina Amaral, et al. (författare)
  • Systems biology approaches to study lipidomes in health and disease
  • 2021
  • Ingår i: Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids. - : Elsevier. - 1388-1981 .- 1879-2618. ; 1866:2
  • Forskningsöversikt (refereegranskat)abstract
    • Lipids have many important biological roles, such as energy storage sources, structural components of plasma membranes and as intermediates in metabolic and signaling pathways. Lipid metabolism is under tight homeostatic control, exhibiting spatial and dynamic complexity at multiple levels. Consequently, lipid-related disturbances play important roles in the pathogenesis of most of the common diseases. Lipidomics, defined as the study of lipidomes in biological systems, has emerged as a rapidly-growing field. Due to the chemical and functional diversity of lipids, the application of a systems biology approach is essential if one is to address lipid functionality at different physiological levels. In parallel with analytical advances to measure lipids in biological matrices, the field of computational lipidomics has been rapidly advancing, enabling modeling of lipidomes in their pathway, spatial and dynamic contexts. This review focuses on recent progress in systems biology approaches to study lipids in health and disease, with specific emphasis on methodological advances and biomedical applications.
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3.
  • Dickens, Alex M., et al. (författare)
  • Links between central CB1-receptor availability and peripheral endocannabinoids in patients with first episode psychosis
  • 2020
  • Ingår i: NPJ schizophrenia. - : Nature Partner Journals. - 2334-265X. ; 6:1
  • Tidskriftsartikel (refereegranskat)abstract
    • There is an established, link between psychosis and metabolic abnormalities, such as altered glucose metabolism and dyslipidemia, which often precede the initiation of antipsychotic treatment. It is known that obesity-associated metabolic disorders are promoted by activation of specific cannabinoid targets (endocannabinoid system (ECS)). Our recent data suggest that there is a change in the circulating lipidome at the onset of first episode psychosis (FEP). With the aim of characterizing the involvement of the central and peripheral ECSs, and their mutual associations; here, we performed a combined neuroimaging and metabolomic study in patients with FEP and healthy controls (HC). Regional brain cannabinoid receptor type 1 (CB1R) availability was quantified in two, independent samples of patients with FEP (n = 20 and n = 8) and HC (n = 20 and n = 10), by applying three-dimensional positron emission tomography, using two radiotracers, [11C]MePPEP and [18F]FMPEP-d2. Ten endogenous cannabinoids or related metabolites were quantified in serum, drawn from these individuals during the same imaging session. Circulating levels of arachidonic acid and oleoylethanolamide (OEA) were reduced in FEP individuals, but not in those who were predominantly medication free. In HC, there was an inverse association between levels of circulating arachidonoyl glycerol, anandamide, OEA, and palmitoyl ethanolamide, and CB1R availability in the posterior cingulate cortex. This phenomenon was, however, not observed in FEP patients. Our data thus provide evidence of cross talk, and dysregulation between peripheral endocannabinoids and central CB1R availability in FEP.
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4.
  • Fang, Wei, et al. (författare)
  • Lipidomes in health and disease : Analytical strategies and considerations
  • 2019
  • Ingår i: TrAC. Trends in analytical chemistry. - : Elsevier. - 0165-9936 .- 1879-3142. ; 120
  • Forskningsöversikt (refereegranskat)abstract
    • Lipidomics is a rapidly-growing field which focuses on global characterization of lipids at molecular and systems levels. As small changes in the concentrations of lipids may have important physiological consequences, much attention in the field has recently been paid to more accurate quantitation and identification of lipids. Community-wide efforts have been initiated, aiming to develop best practices for lipidomic analyses and reporting of lipidomic data. Nevertheless, current approaches for comprehensive analysis of lipidomes have some inherent challenges and limitations. Additionally, there is, currently, limited knowledge concerning the impacts of various external and internal exposures on lipid levels. In this review, we discuss the recent progress in lipidomics analysis, with a primary focus on analytical approaches, as well as on the different sources of variation in quantifying lipid levels, both technical and biological.
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5.
  • Isokääntä, Heidi, et al. (författare)
  • Comparative Metabolomics and Microbiome Analysis of Ethanol versus OMNImet/gene•GUT Fecal Stabilization
  • 2024
  • Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 96:22, s. 8893-9304
  • Tidskriftsartikel (refereegranskat)abstract
    • Metabolites from feces provide important insights into the functionality of the gut microbiome. As immediate freezing is not always feasible in gut microbiome studies, there is a need for sampling protocols that provide the stability of the fecal metabolome and microbiome at room temperature (RT). Here, we investigated the stability of various metabolites and the microbiome (16S rRNA) in feces collected in 95% ethanol (EtOH) and commercially available sample collection kits with specific preservatives OMNImet•GUT/OMNIgene•GUT. To simulate field-collection scenarios, the samples were stored at different temperatures at varying durations (24 h + 4 °C, 24 h RT, 36 h RT, 48 h RT, and 7 days RT) and compared to aliquots immediately frozen at -80 °C. We applied several targeted and untargeted metabolomics platforms to measure lipids, polar metabolites, endocannabinoids, short-chain fatty acids (SCFAs), and bile acids (BAs). We found that SCFAs in the nonstabilized samples increased over time, while a stable profile was recorded in sample aliquots stored in 95% EtOH and OMNImet•GUT. When comparing the metabolite levels between aliquots stored at room temperature and at +4 °C, we detected several changes in microbial metabolites, including multiple BAs and SCFAs. Taken together, we found that storing samples at RT and stabilizing them in 95% EtOH yielded metabolomic results comparable to those from flash freezing. We also found that the overall composition of the microbiome did not vary significantly between different storage types. However, notable differences were observed in the α diversity. Altogether, the stability of the metabolome and microbiome in 95% EtOH provided results similar to those of the validated commercial collection kits OMNImet•GUT and OMNIgene•GUT, respectively.
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6.
  • Kråkström, Matilda, et al. (författare)
  • Dynamics of the Lipidome in a Colon Simulator
  • 2023
  • Ingår i: Metabolites. - : MDPI. - 2218-1989 .- 2218-1989. ; 13:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Current evidence suggests that gut microbiome-derived lipids play a crucial role in the regulation of host lipid metabolism. However, not much is known about the dynamics of gut microbial lipids within the distinct gut biogeographic. Here we applied targeted and untargeted lipidomics to in vitro-derived feces. Simulated intestinal chyme was collected from in vitro gut vessels (V1-V4), representing proximal to distal parts of the colon after 24 and 48 h with/without polydextrose treatment. In total, 44 simulated chyme samples were collected from the in vitro colon simulator. Factor analysis showed that vessel and time had the strongest impact on the simulated intestinal chyme lipid profiles. We found that levels of phosphatidylcholines, sphingomyelins, triacylglycerols, and endocannabinoids were altered in at least one vessel (V1-V4) during simulation. We also found that concentrations of triacylglycerols, diacylglycerols, and endocannabinoids changed with time (24 vs. 48 h of simulation). Together, we found that the simulated intestinal chyme revealed a wide range of lipids that remained altered in different compartments of the human colon model over time.
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7.
  • Lamichhane, Santosh, et al. (författare)
  • A longitudinal plasma lipidomics dataset from children who developed islet autoimmunity and type 1 diabetes
  • 2018
  • Ingår i: Scientific Data. - : Springer Nature. - 2052-4463. ; 5
  • Tidskriftsartikel (refereegranskat)abstract
    • Early prediction and prevention of type 1 diabetes (T1D) are currently unmet medical needs. Previous metabolomics studies suggest that children who develop T1D are characterised by a distinct metabolic profile already detectable during infancy, prior to the onset of islet autoimmunity. However, the specificity of persistent metabolic disturbances in relation T1D development has not yet been established. Here, we report a longitudinal plasma lipidomics dataset from (1) 40 children who progressed to T1D during follow-up, (2) 40 children who developed single islet autoantibody but did not develop T1D and (3) 40 matched controls (6 time points: 3, 6, 12, 18, 24 and 36 months of age). This dataset may help other researchers in studying age-dependent progression of islet autoimmunity and T1D as well as of the age-dependence of lipidomic profiles in general. Alternatively, this dataset could more broadly used for the development of methods for the analysis of longitudinal multivariate data.
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8.
  • Lamichhane, Santosh, et al. (författare)
  • An Overview of Metabolomics Data Analysis : Current Tools and Future Perspectives
  • 2018
  • Ingår i: Data Analysis for Omic Sciences. - : Elsevier. - 9780444640444 ; , s. 387-413
  • Bokkapitel (refereegranskat)abstract
    • Metabolomics is a study of small molecules in the body and the associated metabolic pathways and is considered to provide a close link between organism's genotype and phenotype. As with other ‘omics’ techniques, metabolomic analysis generates large-scale and complex datasets. Therefore, various data analysis tools are needed to extract biologically relevant information. The data analysis workflows in metabolomics studies are generally complex and involve several steps. In this chapter, we highlight the concept of metabolomics workflow and discuss the data analysis strategies for metabolomics experiments. We also discuss the available tools that can assist in biological interpretation of metabolomics data. We also present an emerging approach of developing genome-scale metabolic models to study cellular metabolism.
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9.
  • Lamichhane, Santosh, et al. (författare)
  • Association Between Circulating Lipids and Future Weight Gain in Individuals With an At-Risk Mental State and in First-Episode Psychosis
  • 2021
  • Ingår i: Schizophrenia Bulletin. - : Oxford University Press. - 0586-7614 .- 1745-1701. ; 47:1, s. 160-169
  • Tidskriftsartikel (refereegranskat)abstract
    • Patients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic comorbidities. There is an unmet public health need to identify individuals with psychotic disorders who have a high risk of rapid weight gain and who are at risk of developing metabolic complications. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 healthy controls (CTR), 44 first-episode psychosis (FEP) patients, and 22 individuals at clinical high risk (CHR) for psychosis, from 2 study centers (Turku, Finland and London, UK). Baseline serum samples were analyzed using lipidomics, and body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols (TGs) with low double-bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of 2 TGs (TG[48:0] and TG[45:0]) was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60-0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61-0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic comorbidities.
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10.
  • Lamichhane, Santosh, et al. (författare)
  • Circulating metabolic signatures of rapid and slow progression to type 1 diabetes in islet autoantibody-positive children
  • 2023
  • Ingår i: Frontiers in Endocrinology. - : Frontiers Media S.A.. - 1664-2392. ; 14
  • Tidskriftsartikel (refereegranskat)abstract
    • AIMS/HYPOTHESIS: Appearance of multiple islet cell autoantibodies in early life is indicative of future progression to overt type 1 diabetes, however, at varying rates. Here, we aimed to study whether distinct metabolic patterns could be identified in rapid progressors (RP, disease manifestation within 18 months after the initial seroconversion to autoantibody positivity) vs. slow progressors (SP, disease manifestation at 60 months or later from the appearance of the first autoantibody).METHODS: Longitudinal samples were collected from RP (n=25) and SP (n=41) groups at the ages of 3, 6, 12, 18, 24, or ≥ 36 months. We performed a comprehensive metabolomics study, analyzing both polar metabolites and lipids. The sample series included a total of 239 samples for lipidomics and 213 for polar metabolites.RESULTS: We observed that metabolites mediated by gut microbiome, such as those involved in tryptophan metabolism, were the main discriminators between RP and SP. The study identified specific circulating molecules and pathways, including amino acid (threonine), sugar derivatives (hexose), and quinic acid that may define rapid vs. slow progression to type 1 diabetes. However, the circulating lipidome did not appear to play a major role in differentiating between RP and SP.CONCLUSION/INTERPRETATION: Our study suggests that a distinct metabolic profile is linked with the type 1 diabetes progression. The identification of specific metabolites and pathways that differentiate RP from SP may have implications for early intervention strategies to delay the development of type 1 diabetes.
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11.
  • Lamichhane, Santosh, et al. (författare)
  • Circulating metabolites in progression to islet autoimmunity and type 1 diabetes
  • 2019
  • Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 62:12, s. 2287-2297
  • Tidskriftsartikel (refereegranskat)abstract
    • AIMS/HYPOTHESIS: Metabolic dysregulation may precede the onset of type 1 diabetes. However, these metabolic disturbances and their specific role in disease initiation remain poorly understood. In this study, we examined whether children who progress to type 1 diabetes have a circulatory polar metabolite profile distinct from that of children who later progress to islet autoimmunity but not type 1 diabetes and a matched control group.METHODS: We analysed polar metabolites from 415 longitudinal plasma samples in a prospective cohort of children in three study groups: those who progressed to type 1 diabetes; those who seroconverted to one islet autoantibody but not to type 1 diabetes; and an antibody-negative control group. Metabolites were measured using two-dimensional GC high-speed time of flight MS.RESULTS: In early infancy, progression to type 1 diabetes was associated with downregulated amino acids, sugar derivatives and fatty acids, including catabolites of microbial origin, compared with the control group. Methionine remained persistently upregulated in those progressing to type 1 diabetes compared with the control group and those who seroconverted to one islet autoantibody. The appearance of islet autoantibodies was associated with decreased glutamic and aspartic acids.CONCLUSIONS/INTERPRETATION: Our findings suggest that children who progress to type 1 diabetes have a unique metabolic profile, which is, however, altered with the appearance of islet autoantibodies. Our findings may assist with early prediction of the disease.
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12.
  • Lamichhane, Santosh, et al. (författare)
  • Cord-Blood Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes
  • 2019
  • Ingår i: Biomolecules. - : MDPI. - 2218-273X. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Previous studies suggest that children who progress to type 1 diabetes (T1D) later in life already have an altered serum lipid molecular profile at birth. Here, we compared cord blood lipidome across the three study groups: children who progressed to T1D (PT1D; n = 30), children who developed at least one islet autoantibody but did not progress to T1D during the follow-up (P1Ab; n = 33), and their age-matched controls (CTR; n = 38). We found that phospholipids, specifically sphingomyelins, were lower in T1D progressors when compared to P1Ab and the CTR. Cholesterol esters remained higher in PT1D when compared to other groups. A signature comprising five lipids was predictive of the risk of progression to T1D, with an area under the receiver operating characteristic curve (AUROC) of 0.83. Our findings provide further evidence that the lipidomic profiles of newborn infants who progress to T1D later in life are different from lipidomic profiles in P1Ab and CTR.
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13.
  • Lamichhane, Santosh, et al. (författare)
  • Dynamics of Plasma Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes - Type 1 Diabetes Prediction and Prevention Study (DIPP)
  • 2018
  • Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 8
  • Tidskriftsartikel (refereegranskat)abstract
    • Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that distinct lipidomic signatures characterize children who progressed to islet autoimmunity or overt T1D, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.
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14.
  • Lamichhane, Santosh, et al. (författare)
  • Dysregulation of secondary bile acid metabolism precedes islet autoimmunity and type 1 diabetes
  • 2022
  • Ingår i: Cell Reports Medicine. - : Cell Press. - 2666-3791. ; 3:10
  • Tidskriftsartikel (refereegranskat)abstract
    • The gut microbiota is crucial in the regulation of bile acid (BA) metabolism. However, not much is known about the regulation of BAs during progression to type 1 diabetes (T1D). Here, we analyzed serum and stool BAs in longitudinal samples collected at 3, 6, 12, 18, 24, and 36 months of age from children who developed a single islet autoantibody (AAb) (P1Ab; n = 23) or multiple islet AAbs (P2Ab; n = 13) and controls (CTRs; n = 38) who remained AAb negative. We also analyzed the stool microbiome in a subgroup of these children. Factor analysis showed that age had the strongest impact on both BA and microbiome profiles. We found that at an early age, systemic BAs and microbial secondary BA pathways were altered in the P2Ab group compared with the P1Ab and CTR groups. Our findings thus suggest that dysregulated BA metabolism in early life may contribute to the risk and pathogenesis of T1D.
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15.
  • Lamichhane, Santosh, et al. (författare)
  • Exposure to per- and polyfluoroalkyl substances associates with an altered lipid composition of breast milk
  • 2021
  • Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 157
  • Tidskriftsartikel (refereegranskat)abstract
    • The composition of human breast milk is highly variable inter- and intra-individually. Environmental factors are suspected to contribute to such compositional variation, however, their impact on breast milk composition is currently poorly understood. We sought to (1) define the impact of maternal exposure to per- and polyfluoroalkyl substances (PFAS) on lipid composition of human breast milk, and (2) to study the combined impact of maternal PFAS exposure and breast milk lipid composition on the growth of the infants.In a mother-infant study (n = 44) we measured the levels of PFAS and lipids in maternal serum and conducted lipidomics analysis of breast milk collect 2-4 days after the delivery and at 3 months of infant age, by using ultra high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry. Gastrointestinal biomarkers fecal calprotectin and human beta defensin 2 were measured in the stool samples at the age of 3, 6, 9, and 12 months. Maternal diet was studied by a validated food frequency questionnaire. PFAS levels were inversely associated with total lipid levels in the breast milk collected after the delivery. In the high exposure group, the ratio of acylated saturated and polyunsaturated fatty acids in triacylglycerols was increased. Moreover, high exposure to PFAS associated with the altered phospholipid composition, which was indicative of unfavorable increase in the size of milk fat globules. These changes in the milk lipid composition were further associated with slower infant growth and with elevated intestinal inflammatory markers. Our data suggest that the maternal exposure to PFAS impacts the nutritional quality of the breast milk, which, in turn, may have detrimental impact on the health and growth of the children later in life.
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16.
  • Lamichhane, Santosh, et al. (författare)
  • Gut metabolome meets microbiome : A methodological perspective to understand the relationship between host and microbe
  • 2018
  • Ingår i: Methods. - : Academic Press. - 1046-2023 .- 1095-9130. ; 149, s. 3-12
  • Forskningsöversikt (refereegranskat)abstract
    • It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted.
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17.
  • Lamichhane, Santosh, et al. (författare)
  • Impact of exposure to per- and polyfluoroalkyl substances on fecal microbiota composition in mother-infant dyads
  • 2023
  • Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 176
  • Tidskriftsartikel (refereegranskat)abstract
    • There is growing evidence suggesting that chemical exposure alters gut microbiota composition. However, not much is known about the impact of per- and polyfluoroalkyl substances (PFAS) on the gut microbial community. Here, in a mother-infant study, we set out to identify the gut bacterial species that associate with chemical exposure before (maternal) and after (maternal, infant) birth. Paired serum and stool samples were collected from mother-infant dyads (n = 30) in a longitudinal setting. PFAS were quantified in maternal serum to examine their associations with the microbial compositions (determined by shotgun metagenomic sequencing) in mothers and infants. High maternal exposure to PFAS was consistently associated with increased abundance of Methanobrevibacter smithii in maternal stool. Among individual PFAS compounds, PFOS and PFHpS showed the strongest association with M. smithii. However, maternal total PFAS exposure associated only weakly with the infant microbiome. Our findings suggest that PFAS exposure affects the composition of the adult gut microbiome.
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18.
  • Lamichhane, Santosh, et al. (författare)
  • Impact of Extensively Hydrolyzed Infant Formula on Circulating Lipids During Early Life
  • 2022
  • Ingår i: Frontiers in Nutrition. - : Frontiers Media S.A.. - 2296-861X. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Current evidence suggests that the composition of infant formula (IF) affects the gut microbiome, intestinal function, and immune responses during infancy. However, the impact of IF on circulating lipid profiles in infants is still poorly understood. The objectives of this study were to (1) investigate how extensively hydrolyzed IF impacts serum lipidome compared to conventional formula and (2) to associate changes in circulatory lipids with gastrointestinal biomarkers including intestinal permeability.Methods: In a randomized, double-blind controlled nutritional intervention study (n = 73), we applied mass spectrometry-based lipidomics to analyze serum lipids in infants who were fed extensively hydrolyzed formula (HF) or conventional, regular formula (RF). Serum samples were collected at 3, 9, and 12 months of age. Child's growth (weight and length) and intestinal functional markers, including lactulose mannitol (LM) ratio, fecal calprotectin, and fecal beta-defensin, were also measured at given time points. At 3 months of age, stool samples were analyzed by shotgun metagenomics.Results: Concentrations of sphingomyelins were higher in the HF group as compared to the RF group. Triacylglycerols (TGs) containing saturated and monounsaturated fatty acyl chains were found in higher levels in the HF group at 3 months, but downregulated at 9 and 12 months of age. LM ratio was lower in the HF group at 9 months of age. In the RF group, the LM ratio was positively associated with ether-linked lipids. Such an association was, however, not observed in the HF group.Conclusion: Our study suggests that HF intervention changes the circulating lipidome, including those lipids previously found to be associated with progression to islet autoimmunity or overt T1D.Clinical Trial Registration: [Clinicaltrials.gov], identifier [NCT01735123].
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19.
  • Lamichhane, Santosh, et al. (författare)
  • Linking Gut Microbiome and Lipid Metabolism : Moving beyond Associations
  • 2021
  • Ingår i: Metabolites. - : MDPI. - 2218-1989 .- 2218-1989. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Various studies aiming to elucidate the role of the gut microbiome-metabolome co-axis in health and disease have primarily focused on water-soluble polar metabolites, whilst non-polar microbial lipids have received less attention. The concept of microbiota-dependent lipid biotransformation is over a century old. However, only recently, several studies have shown how microbial lipids alter intestinal and circulating lipid concentrations in the host, thus impacting human lipid homeostasis. There is emerging evidence that gut microbial communities play a particularly significant role in the regulation of host cholesterol and sphingolipid homeostasis. Here, we review and discuss recent research focusing on microbe-host-lipid co-metabolism. We also discuss the interplay of human gut microbiota and molecular lipids entering host systemic circulation, and its role in health and disease.
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20.
  • Mathema, Vivek Bhakta, et al. (författare)
  • Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine
  • 2023
  • Ingår i: Computational and Structural Biotechnology Journal. - : Elsevier. - 2001-0370. ; 21, s. 1372-1382
  • Forskningsöversikt (refereegranskat)abstract
    • Cancer progression is linked to gene-environment interactions that alter cellular homeostasis. The use of biomarkers as early indicators of disease manifestation and progression can substantially improve diagnosis and treatment. Large omics datasets generated by high-throughput profiling technologies, such as microarrays, RNA sequencing, whole-genome shotgun sequencing, nuclear magnetic resonance, and mass spectrometry, have enabled data-driven biomarker discoveries. The identification of differentially expressed traits as molecular markers has traditionally relied on statistical techniques that are often limited to linear parametric modeling. The heterogeneity, epigenetic changes, and high degree of polymorphism observed in oncogenes demand biomarker-assisted personalized medication schemes. Deep learning (DL), a major subunit of machine learning (ML), has been increasingly utilized in recent years to investigate various diseases. The combination of ML/DL approaches for performance optimization across multi-omics datasets produces robust ensemble-learning prediction models, which are becoming useful in precision medicine. This review focuses on the recent development of ML/DL methods to provide integrative solutions in discovering cancer-related biomarkers, and their utilization in precision medicine.
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21.
  • McGlinchey, Aidan J, 1984-, et al. (författare)
  • Prenatal exposure to perfluoroalkyl substances modulates neonatal serum phospholipids, increasing risk of type 1 diabetes
  • 2020
  • Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 143
  • Tidskriftsartikel (refereegranskat)abstract
    • In the last decade, increasing incidence of type 1 diabetes (T1D) stabilized in Finland, a phenomenon that coincides with tighter regulation of perfluoroalkyl substances (PFAS). Here, we quantified PFAS to examine their effects, during pregnancy, on lipid and immune-related markers of T1D risk in children. In a mother-infant cohort (264 dyads), high PFAS exposure during pregnancy associated with decreased cord serum phospholipids and progression to T1D-associated islet autoantibodies in the offspring. This PFAS-lipid association appears exacerbated by increased human leukocyte antigen-conferred risk of T1D in infants. Exposure to a single PFAS compound or a mixture of organic pollutants in non-obese diabetic mice resulted in a lipid profile characterized by a similar decrease in phospholipids, a marked increase of lithocholic acid, and accelerated insulitis. Our findings suggest that PFAS exposure during pregnancy contributes to risk and pathogenesis of T1D in offspring.
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22.
  • Monfort-Pires, Milena, et al. (författare)
  • Classification of Common Food Lipid Sources Regarding Healthiness Using Advanced Lipidomics : A Four-Arm Crossover Study
  • 2023
  • Ingår i: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 24:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Prospective studies have failed to establish a causal relationship between animal fat intake and cardiovascular diseases in humans. Furthermore, the metabolic effects of different dietary sources remain unknown. In this four-arm crossover study, we investigated the impact of consuming cheese, beef, and pork meat on classic and new cardiovascular risk markers (obtained from lipidomics) in the context of a healthy diet. A total of 33 young healthy volunteers (23 women/10 men) were assigned to one out of four test diets in a Latin square design. Each test diet was consumed for 14 days, with a 2-week washout. Participants received a healthy diet plus Gouda- or Goutaler-type cheeses, pork, or beef meats. Before and after each diet, fasting blood samples were withdrawn. A reduction in total cholesterol and an increase in high density lipoprotein particle size were detected after all diets. Only the pork diet upregulated plasma unsaturated fatty acids and downregulated triglycerides species. Improvements in the lipoprotein profile and upregulation of circulating plasmalogen species were also observed after the pork diet. Our study suggests that, within the context of a healthy diet rich in micronutrients and fiber, the consumption of animal products, in particular pork meat, may not induce deleterious effects, and reducing the intake of animal products should not be regarded as a way of reducing cardiovascular risk in young individuals.
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23.
  • Sen, Partho, 1983-, et al. (författare)
  • Deep learning meets metabolomics : a methodological perspective
  • 2021
  • Ingår i: Briefings in Bioinformatics. - : Oxford University Press. - 1467-5463 .- 1477-4054. ; 22:2, s. 1531-1542
  • Forskningsöversikt (refereegranskat)abstract
    • Deep learning (DL), an emerging area of investigation in the fields of machine learning and artificial intelligence, has markedly advanced over the past years. DL techniques are being applied to assist medical professionals and researchers in improving clinical diagnosis, disease prediction and drug discovery. It is expected that DL will help to provide actionable knowledge from a variety of 'big data', including metabolomics data. In this review, we discuss the applicability of DL to metabolomics, while presenting and discussing several examples from recent research. We emphasize the use of DL in tackling bottlenecks in metabolomics data acquisition, processing, metabolite identification, as well as in metabolic phenotyping and biomarker discovery. Finally, we discuss how DL is used in genome-scale metabolic modelling and in interpretation of metabolomics data. The DL-based approaches discussed here may assist computational biologists with the integration, prediction and drawing of statistical inference about biological outcomes, based on metabolomics data.
  •  
24.
  • Sen, Partho, et al. (författare)
  • Metabolic alterations in immune cells associate with progression to type 1 diabetes
  • 2020
  • Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 63:5, s. 1017-1031
  • Tidskriftsartikel (refereegranskat)abstract
    • AIMS/HYPOTHESIS: Previous metabolomics studies suggest that type 1 diabetes is preceded by specific metabolic disturbances. The aim of this study was to investigate whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children who later develop pancreatic beta cell autoimmunity or overt type 1 diabetes.METHODS: In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who (1) progressed to type 1 diabetes (PT1D, n = 34), (2) seroconverted to ≥1 islet autoantibody without progressing to type 1 diabetes (P1Ab, n = 27) or (3) remained autoantibody negative during follow-up (CTRL, n = 10).RESULTS: During the first year of life, levels of most lipids and polar metabolites were lower in the PT1D and P1Ab groups compared with the CTRL group. Pathway over-representation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were over-represented in PT1D. Genome-scale metabolic models of PBMCs during type 1 diabetes progression were developed by using publicly available transcriptomics data and constrained with metabolomics data from our study. Metabolic modelling confirmed altered ceramide pathways, known to play an important role in immune regulation, as specifically associated with type 1 diabetes progression.CONCLUSIONS/INTERPRETATION: Our data suggest that systemic dysregulation of lipid metabolism, as observed in plasma, may impact the metabolism and function of immune cells during progression to overt type 1 diabetes.DATA AVAILABILITY: The GEMs for PBMCs have been submitted to BioModels (www.ebi.ac.uk/biomodels/), under accession number MODEL1905270001. The metabolomics datasets and the clinical metadata generated in this study were submitted to MetaboLights (https://www.ebi.ac.uk/metabolights/), under accession number MTBLS1015.
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25.
  • Sen, Partho, 1983-, et al. (författare)
  • The Role of Omic Technologies in the Study of the Human Gut Microbiome
  • 2019
  • Ingår i: Reference Module in Food Science. - : Elsevier. - 9780081005965
  • Tidskriftsartikel (refereegranskat)abstract
    • Human gut is colonized by a vast number of microbes known as gut microbiota. The microbiota plays a significant role in the maintenance of health and well-being. A dysbiosis in the microbiota has been associated with the altered metabolism and health disorders. Next-generation sequencing (NGS) aided in taxonomic and functional profiling of the gut microbiome. It has unveiled its richness and diversity. However, little is known about the regulation of microbes in the gut ecosystem, and the underlying interactions with the host. In this chapter, we review recent progress in high-throughput (HT) meta-omics technologies and integrative approaches, with special focus on the utilization of metabolic modeling applied in human along the diet-gut-host axis. We also discuss, how meta-omics and microbiome abundances can be integrated to develop condition-specific gut microbiota models on a genome-scale.
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