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  • 1.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Div Prevent Med, Brigham & Womens Hosp, Boston, MA 02115 USA;Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA 02115 USA.
    Ahluwalia, Tarunveer S.
    Steno Diabet Ctr Copenhagen, Gentofte, Denmark.
    Editorial: The Role of Genetic and Lifestyle Factors in Metabolic Diseases2019In: Frontiers in Endocrinology, E-ISSN 1664-2392, Vol. 10, article id 475Article in journal (Other academic)
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  • 2.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA 02115 USA..
    Arnlov, Johan
    Karolinska Inst, Div Family Med & Primary Care, Dept Neurobiol Care Sci & Soc NVS, S-14152 Stockholm, Sweden.;Dalarna Univ, Sch Hlth & Social Studies, S-79131 Falun, Sweden..
    Larsson, Susanna C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Medical epidemiology. Karolinska Inst, Inst Environm Med, Unit Cardiovasc & Nutr Epidemiol, S-17177 Stockholm, Sweden.;Uppsala Univ, Dept Surg Sci, Unit Med Epidemiol, S-75185 Uppsala, Sweden..
    Genetically Predicted Circulating Copper and Risk of Chronic Kidney Disease: A Mendelian Randomization Study2022In: Nutrients, E-ISSN 2072-6643, Vol. 14, no 3, p. 509-, article id 509Article in journal (Refereed)
    Abstract [en]

    Elevated circulating copper levels have been associated with chronic kidney disease (CKD), kidney damage, and decline in kidney function. Using a two sample Mendelian randomization approach where copper-associated genetic variants were used as instrumental variables, genetically predicted higher circulating copper levels were associated with higher CKD prevalence (odds ratio 1.17; 95% confidence interval 1.04, 1.32; p-value = 0.009). There was suggestive evidence that genetically predicted higher copper was associated with a lower estimated glomerular filtration rate and a more rapid kidney damage decline. In conclusion, we observed that elevated circulating copper levels may be a causal risk factor for CKD.

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  • 3.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Carrasquilla, Germán
    Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
    Langner, Taro
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Menzel, Uwe
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Censin, Jenny C.
    Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; 7Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
    Sayols-Baixeras, Sergi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nguyen, Diem
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Mora, Andrés Martínez
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Eriksson, Jan W.
    Clinical Diabetes and Metabolism, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Genetics of liver fat and volume associate with altered metabolism and whole body magnetic resonance imaging2022In: Journal of Hepatology, ISSN 0168-8278, E-ISSN 1600-0641, Vol. 77, p. S40-S40Article in journal (Other academic)
  • 4.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Medical School; Harvard T.H. Chan School of Public Health.
    Demler, O. V.
    Sun, Q.
    Moorthy, M. V.
    Li, C.
    Lee, I.-M.
    Ridker, P. M.
    Manson, J. E.
    Hu, F. B.
    Fall, Tove
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Chasman, D. I.
    Cheng, S.
    Pradhan, A.
    Mora, S.
    Association of the Mediterranean Diet With Onset of Diabetes in the Women’s Health Study2020In: JAMA Network Open, E-ISSN 2574-3805, Vol. 3, no 11, article id e2025466Article in journal (Refereed)
    Abstract [en]

    Importance  Higher Mediterranean diet (MED) intake has been associated with reduced risk of type 2 diabetes, but underlying biological mechanisms are unclear.

    Objective  To characterize the relative contribution of conventional and novel biomarkers in MED-associated type 2 diabetes risk reduction in a US population.

    Design, Setting, and Participants  This cohort study was conducted among 25 317 apparently healthy women. The participants with missing information regarding all traditional and novel metabolic biomarkers or those with baseline diabetes were excluded. Participants were invited for baseline assessment between September 1992 and May 1995. Data were collected from November 1992 to December 2017 and analyzed from December 2018 to December 2019.

    Exposures  MED intake score (range, 0 to 9) was computed from self-reported dietary intake, representing adherence to Mediterranean diet intake.

    Main Outcomes and Measures  Incident cases of type 2 diabetes, identified through annual questionnaires; reported cases were confirmed by either telephone interview or supplemental questionnaire. Proportion of reduced risk of type 2 diabetes explained by clinical risk factors and a panel of 40 biomarkers that represent different physiological pathways was estimated.

    Results  The mean (SD) age of the 25 317 female participants was 52.9 (9.9) years, and they were followed up for a mean (SD) of 19.8 (5.8) years. Higher baseline MED intake (score ≥6 vs ≤3) was associated with as much as a 30% lower type 2 diabetes risk (age-adjusted and energy-adjusted hazard ratio, 0.70; 95% CI, 0.62-0.79; when regression models were additionally adjusted with body mass index [BMI]: hazard ratio, 0.85; 95% CI, 0.76-0.96). Biomarkers of insulin resistance made the largest contribution to lower risk (accounting for 65.5% of the MED–type 2 diabetes association), followed by BMI (55.5%), high-density lipoprotein measures (53.0%), and inflammation (52.5%), with lesser contributions from branched-chain amino acids (34.5%), very low-density lipoprotein measures (32.0%), low-density lipoprotein measures (31.0%), blood pressure (29.0%), and apolipoproteins (23.5%), and minimal contribution (≤2%) from hemoglobin A1c. In post hoc subgroup analyses, the inverse association of MED diet with type 2 diabetes was seen only among women who had BMI of at least 25 at baseline but not those who had BMI of less than 25 (eg, women with BMI <25, age- and energy-adjusted HR for MED score ≥6 vs ≤3, 1.01; 95% CI, 0.77-1.33; P for trend = .92; women with BMI ≥25: HR, 0.76; 95% CI, 0.67-0.87; P for trend < .001).

    Conclusions and Relevance  In this cohort study, higher MED intake scores were associated with a 30% relative risk reduction in type 2 diabetes during a 20-year period, which could be explained in large part by biomarkers of insulin resistance, BMI, lipoprotein metabolism, and inflammation.

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  • 5.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Prevent Med Div, Brigham & Womens Hosp, Boston, MA 02115 USA;Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA 02115 USA.
    Fatima, Syeda Sadia
    Aga Khan Univ, Dept Biol & Biomed Sci, Karachi, Pakistan.
    Rukh, Gull
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
    Smith, Caren E.
    Tufts Univ, Res Ctr Aging, Jean Mayer US Dept Agr, Nutr & Genom Lab, Boston, MA 02111 USA.
    Gene Lifestyle Interactions With Relation to Obesity, Cardiometabolic, and Cardiovascular Traits Among South Asians2019In: Frontiers in Endocrinology, E-ISSN 1664-2392, Vol. 10, article id 221Article, review/survey (Refereed)
    Abstract [en]

    The rapid rise of obesity, type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) during the last few decades among South Asians has been largely attributed to a major shift in lifestyles including physical inactivity, unhealthy dietary patterns, and an overall pattern of sedentary lifestyle. Genetic predisposition to these cardiometabolic risk factors may have interacted with these obesogenic environments in determining the higher cardiometabolic disease prevalence. Based on the premise that gene-environment interactions cause obesity and cardiometabolic diseases, we systematically searched the literature and considered the knowledge gaps that future studies might ful fill. We identified only seven published studies that focused specifically on gene-environment interactions for cardiometabolic traits in South Asians, most of which were limited by relatively small sample and lack of replication. Some studies reported that the differences in metabolic response to higher physical activity and low caloric diet might be modified by genetic risk related to these cardiometabolic traits. Although studies on gene lifestyle interactions in cardiometabolic traits report significant interactions, future studies must focus on more precise assessment of lifestyle factors, investigation of a larger set of genetic variants and the application of powerful statistical methods to facilitate translatable approaches. Future studies should also be integrated with findings both using mechanistic studies through laboratory settings and randomized clinical trials for clinical outcomes.

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  • 6.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kennedy, Beatrice
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Salihovic, Samira
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. School of Medical Sciences, Örebro University, Örebro, Sweden.
    Ganna, Andrea
    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Sundström, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology. The George Institute for Global Health, Sydney, Australia.
    Ärnlöv, Johan
    Division of and Primary Care, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet; School of Health and Social Studies, Dalarna University.
    Berne, Christian
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Risérus, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism.
    Magnusson, Patrik KE
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet.
    Larsson, Susanna C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Medical epidemiology. Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden..
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Effect of General Adiposity and Central Body Fat Distribution on the Circulating Metabolome: A Multi-Cohort Nontargeted Metabolomics Observational and Mendelian Randomization Study2022In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 71, no 2, p. 329-339Article in journal (Refereed)
    Abstract [en]

    Obesity is associated with adverse health outcomes, but the metabolic effects have not yet been fully elucidated. We aimed to investigate the association between adiposity with circulating metabolites and to address causality with Mendelian randomization (MR). Metabolomics data was generated by non-targeted ultra-performance liquid-chromatography coupled to time-of-flight mass-spectrometry in plasma and serum from three population-based Swedish cohorts: ULSAM (N=1,135), PIVUS (N=970), and TwinGene (N=2,059). We assessed associations between general adiposity measured as body mass index (BMI) and central body fat distribution measured as waist-to-hip ratio adjusted for BMI (WHRadjBMI) with 210 annotated metabolites. We employed MR analysis to assess causal effects. Lastly, we attempted to replicate the MR findings in the KORA and TwinsUK cohorts (N=7,373), the CHARGE consortium (N=8,631), the Framingham Heart Study (N=2,076) and the DIRECT consortium (N=3,029). BMI was associated with 77 metabolites, while WHRadjBMI was associated with 11 and 3 metabolites in women and men, respectively. The MR analyses in the Swedish cohorts suggested a causal association (p-value <0.05) of increased general adiposity and reduced levels of arachidonic acid, dodecanedioic acid and lysophosphatidylcholine (P-16:0) as well as with increased creatine levels. The replication effort provided support for a causal association of adiposity on reduced levels of arachidonic acid (p-value 0.03). Adiposity is associated with variation of large parts of the circulating metabolome, however causality needs further investigation in well-powered cohorts.

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  • 7.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave, Boston, MA 02215 USA;Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA;Harvard Med Sch, Brigham & Womens Hosp, Cardiovasc Div, Boston, MA 02215 USA.
    Moorthy, M. Vinayaga
    Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave, Boston, MA 02215 USA.
    Demler, Olga, V
    Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Cardiovasc Div, Boston, MA 02215 USA.
    Hu, Frank B.
    Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA;Brigham & Womens Hosp, Dept Med, Channing Div Network Med, 75 Francis St, Boston, MA 02115 USA;Harvard Med Sch, Boston, MA 02215 USA.
    Ridker, Paul M.
    Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Cardiovasc Div, Boston, MA 02215 USA.
    Chasman, Daniel, I
    Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA.
    Mora, Samia
    Harvard Med Sch, Brigham & Womens Hosp, Prevent Med Div, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave, Boston, MA 02215 USA;Harvard Med Sch, Brigham & Womens Hosp, Cardiovasc Div, Boston, MA 02215 USA.
    Assessment of Risk Factors and Biomarkers Associated With Risk of Cardiovascular Disease Among Women Consuming a Mediterranean Diet2018In: JAMA Network Open, E-ISSN 2574-3805, Vol. 1, no 8, article id e185708Article in journal (Refereed)
    Abstract [en]

    IMPORTANCE Higher Mediterranean diet (MED) intake has been associated with lower risk of cardiovascular disease (CVD), but limited data are available about the underlying molecular mechanisms of this inverse disease association in human populations.

    OBJECTIVE To better characterize the relative contribution of traditional and novel factors to the MED-related risk reduction in CVD events in a US population.

    DESIGN, SETTING, AND PARTICIPANTS Using a prospective cohort design, baseline MED intake was assessed in 25 994 initially healthy US women in theWomen's Health Study who were followed up to 12 years. Potential mediating effects of a panel of 40 biomarkers were evaluated, including lipids, lipoproteins, apolipoproteins, inflammation, glucose metabolism and insulin resistance, branched-chain amino acids, small-molecule metabolites, and clinical factors. Baseline study information and samples were collected between April 30, 1993, and January 24, 1996. Analyses were conducted between August 1, 2017, and October 30, 2018.

    EXPOSURES Intake of MED is a 9-category measure of adherence to a Mediterranean dietary pattern. Participants were categorized into 3 levels based on their adherence to the MED.

    MAIN OUTCOMES AND MEASURES Incident CVD confirmed through medical records and the proportion of CVD risk reduction explained by mediators.

    RESULTS Among 25 994women (mean [SD] age, 54.7 [7.1] years), those with low, middle, and upper MED intakes composed 39.0%, 36.2%, and 24.8% of the study population and experienced 428 (4.2%), 356 (3.8%), and 246 (3.8%) incident CVD events, respectively. Compared with the reference group who had low MED intake, CVD risk reductions were observed for the middle and upper groups, with respective HRs of 0.77 (95% CI, 0.67-0.90) and 0.72 (95% CI, 0.61-0.86) (P for trend < .001). The largest mediators of the CVD risk reduction of MED intake were biomarkers of inflammation (accounting for 29.2% of the MED-CVD association), glucose metabolism and insulin resistance (27.9%), and body mass index (27.3%), followed by blood pressure (26.6%), traditional lipids (26.0%), high-density lipoprotein measures (24.0%) or very low-density lipoprotein measures (20.8%), with lesser contributions from low-density lipoproteins (13.0%), branched-chain amino acids (13.6%), apolipoproteins (6.5%), or other small-molecule metabolites (5.8%).

    CONCLUSIONS AND RELEVANCE In this study, higher MED intake was associated with approximately one-fourth relative risk reduction in CVD events, which could be explained in part by known risk factors, both traditional and novel.

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  • 8.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave,3rd Floor, Boston, MA 02215 USA.;Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA..
    Moorthy, M. Vinayaga
    Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave,3rd Floor, Boston, MA 02215 USA.;Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA..
    Lee, I-Min
    Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA.;Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA..
    Ridker, Paul M.
    Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA..
    Manson, JoAnn E.
    Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA.;Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA..
    Buring, Julie E.
    Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA.;Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA..
    Demler, Olga V.
    Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave,3rd Floor, Boston, MA 02215 USA.;Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA.;Dept Comp Sci, ETH Zurich, Zurich, Switzerland..
    Mora, Samia
    Harvard Med Sch, Brigham & Womens Hosp, Ctr Lipid Metabol, 900 Commonwealth Ave,3rd Floor, Boston, MA 02215 USA.;Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA USA.;Harvard Med Sch, Brigham & Womens Hosp, Cardiovasc Div, Boston, MA USA..
    Mediterranean Diet Adherence and Risk of All-Cause Mortality in Women2024In: JAMA Network Open, E-ISSN 2574-3805, Vol. 7, no 5, article id e2414322Article in journal (Refereed)
    Abstract [en]

    Importance Higher adherence to the Mediterranean diet has been associated with reduced risk of all-cause mortality, but data on underlying molecular mechanisms over long follow-up are limited. Objectives To investigate Mediterranean diet adherence and risk of all-cause mortality and to examine the relative contribution of cardiometabolic factors to this risk reduction. Design, Setting, and Participants This cohort study included initially healthy women from the Women's Health Study, who had provided blood samples, biomarker measurements, and dietary information. Baseline data included self-reported demographics and a validated food-frequency questionnaire. The data collection period was from April 1993 to January 1996, and data analysis took place from June 2018 to November 2023. Exposures Mediterranean diet score (range, 0-9) was computed based on 9 dietary components. Main Outcome and Measures Thirty-three blood biomarkers, including traditional and novel lipid, lipoprotein, apolipoprotein, inflammation, insulin resistance, and metabolism measurements, were evaluated at baseline using standard assays and nuclear magnetic resonance spectroscopy. Mortality and cause of death were determined from medical and death records. Cox proportional hazards regression was used to calculate hazard ratios (HRs) for Mediterranean diet adherence and mortality risk, and mediation analyses were used to calculate the mediated effect of different biomarkers in understanding this association. Results Among 25 315 participants, the mean (SD) baseline age was 54.6 (7.1) years, with 329 (1.3%) Asian women, 406 (1.6%) Black women, 240 (0.9%) Hispanic women, 24 036 (94.9%) White women, and 95 (0.4%) women with other race and ethnicity; the median (IQR) Mediterranean diet adherence score was 4.0 (3.0-5.0). Over a mean (SD) of 24.7 (4.8) years of follow-up, 3879 deaths occurred. Compared with low Mediterranean diet adherence (score 0-3), adjusted risk reductions were observed for middle (score 4-5) and upper (score 6-9) groups, with HRs of 0.84 (95% CI, 0.78-0.90) and 0.77 (95% CI, 0.70-0.84), respectively (P for trend < .001). Further adjusting for lifestyle factors attenuated the risk reductions, but they remained statistically significant (middle adherence group: HR, 0.92 [95% CI, 0.85-0.99]; upper adherence group: HR, 0.89 [95% CI, 0.82-0.98]; P for trend = .001). Of the biomarkers examined, small molecule metabolites and inflammatory biomarkers contributed most to the lower mortality risk (explaining 14.8% and 13.0%, respectively, of the association), followed by triglyceride-rich lipoproteins (10.2%), body mass index (10.2%), and insulin resistance (7.4%). Other pathways, including branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension, had smaller contributions (<3%). Conclusions and Relevance In this cohort study, higher adherence to the Mediterranean diet was associated with 23% lower risk of all-cause mortality. This inverse association was partially explained by multiple cardiometabolic factors.

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  • 9.
    Ahmad, Shafqat
    et al.
    Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA;Preventive Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
    Mora, Samia
    Preventive Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA;Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA;Center for Lipid Metabolomics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
    Franks, Paul W
    Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA;Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Clinical Research Centre, Lund University, Skåne University Hospital, Malmö, Sweden;Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University, Umeå, Sweden.
    Orho-Melander, Marju
    Diabetes and Cardiovascular Disease–Genetic Epidemiology, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Ridker, Paul M
    Preventive Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA;Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
    Hu, Frank B
    Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA;Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
    Chasman, Daniel I
    Preventive Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
    Adiposity and Genetic Factors in Relation to Triglycerides and Triglyceride-Rich Lipoproteins in the Women's Genome Health Study2018In: Clinical Chemistry, ISSN 0009-9147, E-ISSN 1530-8561, Vol. 64, no 1, p. 231-241Article in journal (Refereed)
    Abstract [en]

    Background: Previous results from Scandinavian cohorts have shown that obesity accentuates the effects of common genetic susceptibility variants on increased triglycerides (TG). Whether such interactions are present in the US population and further selective for particular TG-rich lipoprotein subfractions is unknown.

    Methods: We examined these questions using body mass index (BMI) and waist circumference (WC) among women of European ancestry from the Women's Genome Health Study (WGHS) (n = 21840 for BMI; n = 19313 for WC). A weighted genetic risk score (TG-wGRS) based on 40 published TG-associated single-nucleotide polymorphisms was calculated using published effect estimates.

    Results: Comparing overweight (BMI ≥ 25 kg/m2) and normal weight (BMI < 25 kg/m2) WGHS women, each unit increase of TG-wGRS was associated with TG increases of 1.013% and 1.011%, respectively, and this differential association was significant (Pinteraction = 0.014). Metaanalyses combining results for WGHS BMI with the 4 Scandinavian cohorts (INTER99, HEALTH2006, GLACIER, MDC) (total n = 40026) yielded a more significant interaction (Pinteraction = 0.001). Similarly, we observed differential association of the TG-wGRS with TG (Pinteraction = 0.006) in strata of WC (<80 cm vs ≥80 cm). Metaanalysis with 2 additional cohorts reporting WC (INTER99 and HEALTH2006) (total n = 27834) was significant with consistent effects (Pinteraction = 0.006). We also observed highly significant interactions of the TG-wGRS across the strata of BMI with very large, medium, and small TG-rich lipoprotein subfractions measured by nuclear magnetic resonance spectroscopy (all Pinteractions < 0.0001). The differential effects were strongest for very large TG-rich lipoprotein.

    Conclusions: Our results support the original findings and suggest that obese individuals may be more susceptible to aggregated genetic risk associated with common TG-raising alleles, with effects accentuated in the large TG-rich lipoprotein subfraction.

  • 10.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA;Harvard Med Sch, Div Prevent Med, Boston, MA USA.
    Mora, Samia
    Harvard Med Sch, Div Prevent Med, Boston, MA USA;Harvard Med Sch, Cardiovasc Div, Boston, MA USA;Harvard Med Sch, Ctr Lipid Metabol, Boston, MA USA.
    Ridker, Paul M.
    Harvard Med Sch, Div Prevent Med, Boston, MA USA;Harvard Med Sch, Cardiovasc Div, Boston, MA USA;Harvard Med Sch, Ctr Lipid Metabol, Boston, MA USA.
    Hu, Frank B.
    Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA;Harvard Med Sch, Brigham & Womens Hosp, Dept Med, Div Network Med, Boston, MA USA.
    Chasman, Daniel I.
    Harvard Med Sch, Div Prevent Med, Boston, MA USA.
    Gene-Based Elevated Triglycerides and Type 2 Diabetes Mellitus Risk in the Women's Genome Health Study2019In: Arteriosclerosis, Thrombosis and Vascular Biology, ISSN 1079-5642, E-ISSN 1524-4636, Vol. 39, no 1, p. 97-106Article in journal (Refereed)
    Abstract [en]

    Objective- Higher triglyceride (TG) is a risk factor for incident type 2 diabetes mellitus (T2DM), but paradoxically, genetic susceptibility for higher TG has been associated with lower T2DM risk. There is also evidence that the genetic association may be modified by baseline TG. Whether such associations can be replicated and the interaction is selective for certain TG-rich lipoprotein particles remains to be explored.

    Approach and Results-Cox regression involving TG, TG-rich lipoprotein particles, and genetic determinants of TG was performed among 15 813 participants with baseline fasting status in the WGHS (Women's Genome Health Study), including 1453 T2DM incident cases during a mean 18.6 (SD= 5.3) years of follow-up. A weighted, 40-single-nucleotide polymorphism TG genetic risk score was inversely associated with incident T2DM (hazard ratio [95% CI], 0.66 [0.580.75]/ 10-TG risk alleles; P< 0.0001) with adjustment for baseline body mass index, HDL (high-density lipoprotein) cholesterol, and TG. TG-associated risk was higher among individuals in the low compared with the high 40-singlenucleotide polymorphism TG genetic risk score tertile (hazard ratio [95% CI], 1.98 [1.83-2.14] versus 1.68 [1.58-1.80] per mmol/L; P-interaction = 0.0007). In TG-adjusted analysis, large and medium but not small TG-rich lipoprotein particles were associated with higher T2DM incidence for successively lower 40-single-nucleotide polymorphism TG genetic risk score tertiles, P-interaction = 0.013, 0.012, and 0.620 across tertiles, respectively.

    Conclusions-Our results confirm the previous observations of the paradoxical associations of TG with T2DM while focusing attention on the larger TG-rich lipoprotein particle subfractions, suggesting their importance in clinical profiling of T2DM risk.

  • 11.
    Ali, Mohammed K.
    et al.
    Hubert Department of Global Health Rollins School of Public Health, Emory University Atlanta Georgia USA;Department of Family and Preventive Medicine School of Medicine, Emory University Atlanta Georgia USA.
    Kadir, M. Masood
    Department of Community Health Sciences Aga Khan University Karachi Pakistan.
    Gujral, Unjali P.
    Hubert Department of Global Health Rollins School of Public Health, Emory University Atlanta Georgia USA.
    Fatima, Syeda Sadia
    Department of Biological and Biomedical Sciences Aga Khan University Karachi Pakistan.
    Iqbal, Romaina
    Department of Community Health Sciences Aga Khan University Karachi Pakistan.
    Sun, Yan V.
    Department of Epidemiology Rollins School of Public Health, Emory University Atlanta Georgia USA.
    Narayan, K. M. Venkat
    Hubert Department of Global Health Rollins School of Public Health, Emory University Atlanta Georgia USA;Department of Epidemiology Rollins School of Public Health, Emory University Atlanta Georgia USA.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Preventive Medicine Division Harvard Medical School, Brigham and Women's Hospital Boston Massachusetts USA.
    Obesity‐associated metabolites in relation to type 2 diabetes risk: A prospective nested case‐control study of the CARRS cohort2022In: Diabetes, obesity and metabolism, ISSN 1462-8902, E-ISSN 1463-1326, Vol. 24, no 10, p. 2008-2016Article in journal (Refereed)
    Abstract [en]

    Aims: To determine whether obesity-associated metabolites are associated with type 2 diabetes (T2DM) risk among South Asians.

    Materials and methods: Serum-based nuclear magnetic resonance imaging metabolomics data were generated from two South Asian population-based prospective cohorts from Karachi, Pakistan: CARRS1 (N = 4017) and CARRS2 (N = 4802). Participants in both cohorts were followed up for 5 years and incident T2DM was ascertained. A nested case-control study approach was developed to select participants from CARRS1 (Ncases = 197 and Ncontrols = 195) and CARRS2 (Ncases = 194 and Ncontrols = 200), respectively. First, we investigated the association of 224 metabolites with general obesity based on body mass index and with central obesity based on waist-hip ratio, and then the top obesity-associated metabolites were studied in relation to incident T2DM.

    Results: In a combined sample of the CARRS1 and CARRS2 cohorts, out of 224 metabolites, 12 were associated with general obesity and, of these, one was associated with incident T2DM. Fifteen out of 224 metabolites were associated with central obesity and, of these, 10 were associated with incident T2DM. The higher level of total cholesterol in high-density lipoprotein (HDL) was associated with reduced T2DM risk (odds ratio [OR] 0.68, 95% confidence interval [CI] 0.53, 0.86; P = 1.2 × 10-3 ), while higher cholesterol esters in large very-low-density lipoprotein (VLDL) particles were associated with increased T2DM risk (OR 1.90, 95% CI 1.40, 2.58; P = 3.5 × 10-5 ).

    Conclusion: Total cholesterol in HDL and cholesterol esters in large VLDL particles may be an important biomarker in the identification of early development of obesity-associated T2DM risk among South Asian adults.

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  • 12.
    Baldanzi, Gabriel
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Sayols-Baixeras, Sergi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Ekblom-Bak, Elin
    Ekblom, Örjan
    Dekkers, Koen F.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Nguyen, Diem
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Preventive Medicine Division, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, United States.
    Ericson, Ulrika
    Arvidsson, Daniel
    Börjesson, Mats
    Johansson, Peter J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Occupational and Environmental Medicine. Occupational and Environmental Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Smith, J. Gustav
    Bergström, Göran
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Engström, Gunnar
    Ärnlöv, Johan
    Kennedy, Beatrice
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Orho-Melander, Marju
    Fall, Tove
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Accelerometer-based physical activity is associated with the gut microbiota in 8416 individuals in SCAPIS2024In: EBioMedicine, E-ISSN 2352-3964, Vol. 100, article id 104989Article in journal (Refereed)
    Abstract [en]

    Background

    Previous population-based studies investigating the relationship between physical activity and the gut microbiota have relied on self-reported activity, prone to reporting bias. Here, we investigated the associations of accelerometer-based sedentary (SED), moderate-intensity (MPA), and vigorous-intensity (VPA) physical activity with the gut microbiota using cross-sectional data from the Swedish CArdioPulmonary bioImage Study.

    Methods

    In 8416 participants aged 50–65, time in SED, MPA, and VPA were estimated with hip-worn accelerometer. Gut microbiota was profiled using shotgun metagenomics of faecal samples. We applied multivariable regression models, adjusting for sociodemographic, lifestyle, and technical covariates, and accounted for multiple testing.

    Findings

    Overall, associations between time in SED and microbiota species abundance were in opposite direction to those for MPA or VPA. For example, MPA was associated with lower, while SED with higher abundance of Escherichia coli. MPA and VPA were associated with higher abundance of the butyrate-producers Faecalibacterium prausnitzii and Roseburia spp. We observed discrepancies between specific VPA and MPA associations, such as a positive association between MPA and Prevotella copri, while no association was detected for VPA. Additionally, SED, MPA and VPA were associated with the functional potential of the microbiome. For instance, MPA was associated with higher capacity for acetate synthesis and SED with lower carbohydrate degradation capacity.

    Interpretation

    Our findings suggest that sedentary and physical activity are associated with a similar set of gut microbiota species but in opposite directions. Furthermore, the intensity of physical activity may have specific effects on certain gut microbiota species.

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    Accelerometer-based physical activity is associated with the gut microbiota in 8416 individuals in SCAPIS
  • 13.
    Baldanzi, Gabriel
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sayols-Baixeras, Sergi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. CIBER Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain.
    Theorell-Haglöw, Jenny
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Lung- allergy- and sleep research.
    Dekkers, Koen F.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nguyen, Diem
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Lin, Yi-Ting
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institute, Huddinge, Sweden; Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Taiwan.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Preventive Medicine Division, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA.
    Bak Holm, Jacob
    Nielsen, Henrik Bjørn
    Brunkwall, Louise
    Benedict, Christian
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Cedernaes, Jonathan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Transplantation and regenerative medicine. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Koskiniemi, Sanna
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology and Immunology.
    Phillipson, Mia
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology, Integrative Physiology.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Sundström, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology. The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.
    Bergström, Göran
    Engström, Gunnar
    Smith, J. Gustav
    Orho-Melander, Marju
    Ärnlöv, Johan
    Kennedy, Beatrice
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lindberg, Eva
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Lung- allergy- and sleep research.
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    OSA Is Associated With the Human Gut Microbiota Composition and Functional Potential in the Population-Based Swedish CardioPulmonary bioImage Study2023In: Chest, ISSN 0012-3692, E-ISSN 1931-3543, Vol. 164, no 2, p. 503-516Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Obstructive sleep apnea (OSA) is a common sleep-breathing disorder linked to increased risk of cardiovascular disease. Intermittent hypoxia and intermittent airway obstruction, hallmarks of OSA, have been shown in animal models to induce substantial changes to the gut microbiota composition and subsequent transplantation of fecal matter to other animals induced changes in blood pressure and glucose metabolism.

    RESEARCH QUESTION: Does obstructive sleep apnea in adults associate with the composition and metabolic potential of the human gut microbiota?

    STUDY DESIGN AND METHODS: We used respiratory polygraphy data from up to 3,570 individuals aged 50-64 from the population-based Swedish CardioPulmonary bioImage Study combined with deep shotgun metagenomics of fecal samples to identify cross-sectional associations between three OSA parameters covering apneas and hypopneas, cumulative sleep time in hypoxia and number of oxygen desaturation events with gut microbiota composition. Data collection about potential confounders was based on questionnaires, on-site anthropometric measurements, plasma metabolomics, and linkage with the Swedish Prescribed Drug Register.

    RESULTS: We found that all three OSA parameters were associated with lower diversity of species in the gut. Further, the OSA-related hypoxia parameters were in multivariable-adjusted analysis associated with the relative abundance of 128 gut bacterial species, including higher abundance of Blautia obeum and Collinsela aerofaciens. The latter species was also independently associated with increased systolic blood pressure. Further, the cumulative time in hypoxia during sleep was associated with the abundance of genes involved in nine gut microbiota metabolic pathways, including propionate production from lactate. Lastly, we observed two heterogeneous sets of plasma metabolites with opposite association with species positively and negatively associated with hypoxia parameters, respectively.

    INTERPRETATION: OSA-related hypoxia, but not the number of apneas/hypopneas, is associated with specific gut microbiota species and functions. Our findings lay the foundation for future research on the gut microbiota-mediated health effects of OSA.

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  • 14.
    Dekkers, Koen
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sayols-Baixeras, Sergi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Inst Salud Carlos III, CIBER Cardiovasc Dis CIBERCV, Madrid, Spain..
    Baldanzi, Gabriel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nowak, Christoph
    Karolinska Inst, Dept Neurobiol Care Sci & Soc, Div Family Med & Primary Care, Huddinge, Sweden..
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nguyen, Diem
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Varotsis, Georgios
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Brunkwall, Louise
    Lund Univ, Dept Clin Sci, Malmö, Sweden..
    Nielsen, Nynne
    Clin Microbi AS, Copenhagen, Denmark..
    Eklund, Aron C.
    Clin Microbi AS, Copenhagen, Denmark..
    Holm, Jacob Bak
    Clin Microbi AS, Copenhagen, Denmark..
    Nielsen, H. Bjorn
    Clin Microbi AS, Copenhagen, Denmark..
    Ottosson, Filip
    Lund Univ, Dept Clin Sci, Malmö, Sweden..
    Yi-Ting, Lin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Sundström, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology. Univ New South Wales, George Inst Global Hlth, Sydney, NSW, Australia..
    Engstrom, Gunnar
    Lund Univ, Dept Clin Sci, Malmö, Sweden..
    Smith, J. Gustav
    Gothenburg Univ, Inst Med, Dept Mol & Clin Med, Wallenberg Lab, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Dept Cardiol, Gothenburg, Sweden.;Lund Univ, Clin Sci, Dept Cardiol, Lund, Sweden.;Skane Univ Hosp, Lund, Sweden.;Lund Univ, Wallenberg Ctr Mol Med, Lund, Sweden.;Lund Univ, Diabet Ctr, Lund, Sweden..
    Arnlov, Johan
    Karolinska Inst, Dept Neurobiol Care Sci & Soc, Div Family Med & Primary Care, Huddinge, Sweden.;Dalarna Univ, Sch Hlth & Social Studies, Falun, Sweden..
    Orho-Melander, Marju
    Lund Univ, Dept Clin Sci, Malmö, Sweden..
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    An online atlas of human plasma metabolite signatures of gut microbiome composition2022In: Nature Communications, E-ISSN 2041-1723, Vol. 13, no 1, article id 5370Article in journal (Refereed)
    Abstract [en]

    Human gut microbiota produce a variety of molecules, some of which enter the bloodstream and impact health. Conversely, dietary or pharmacological compounds may affect the microbiota before entering the circulation. Characterization of these interactions is an important step towards understanding the effects of the gut microbiota on health. In this cross-sectional study, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for a detailed characterization of the gut microbiota and plasma metabolome, respectively, of 8583 participants invited at age 50 to 64 from the population-based Swedish CArdioPulmonary bioImage Study. Here, we find that the gut microbiota explain up to 58% of the variance of individual plasma metabolites and we present 997 associations between alpha diversity and plasma metabolites and 546,819 associations between specific gut metagenomic species and plasma metabolites in an online atlas (https://gutsyatlas.serve.scilifelab.se/). We exemplify the potential of this resource by presenting novel associations between dietary factors and oral medication with the gut microbiome, and microbial species strongly associated with the uremic toxin p-cresol sulfate. This resource can be used as the basis for targeted studies of perturbation of specific metabolites and for identification of candidate plasma biomarkers of gut microbiota composition.

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  • 15. Ding, Ming
    et al.
    Ahmad, Shafqat
    Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA;Division of Preventive Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA.
    Qi, Lu
    Hu, Yang
    Bhupathiraju, Shilpa N
    Guasch-Ferré, Marta
    Jensen, Majken K
    Chavarro, Jorge E
    Ridker, Paul M
    Willett, Walter C
    Chasman, Daniel I
    Hu, Frank B
    Kraft, Peter
    Additive and Multiplicative Interactions Between Genetic Risk Score and Family History and Lifestyle in Relation to Risk of Type 2 Diabetes2020In: American Journal of Epidemiology, ISSN 0002-9262, E-ISSN 1476-6256, Vol. 189, no 5, p. 445-460Article in journal (Refereed)
    Abstract [en]

    We examined interactions between lifestyle factors and genetic risk of type 2 diabetes (T2D-GR), captured by genetic risk score (GRS) and family history (FH). Our initial study cohort included 20,524 European-ancestry participants, of whom 1,897 developed incident T2D, in the Nurses' Health Study (1984-2016), Nurses' Health Study II (1989-2016), and Health Professionals Follow-up Study (1986-2016). The analyses were replicated in 19,183 European-ancestry controls and 2,850 incident T2D cases in the Women's Genome Health Study (1992-2016). We defined 2 categories of T2D-GR: high GRS (upper one-third) with FH and low GRS or without FH. Compared with participants with the healthiest lifestyle and low T2D-GR, the relative risk of T2D for participants with the healthiest lifestyle and high T2D-GR was 2.24 (95% confidence interval (CI): 1.76, 2.86); for participants with the least healthy lifestyle and low T2D-GR, it was 4.05 (95% CI: 3.56, 4.62); and for participants with the least healthy lifestyle and high T2D-GR, it was 8.72 (95% CI: 7.46, 10.19). We found a significant departure from an additive risk difference model in both the initial and replication cohorts, suggesting that adherence to a healthy lifestyle could lead to greater absolute risk reduction among those with high T2D-GR. The public health implication is that a healthy lifestyle is important for diabetes prevention, especially for individuals with high GRS and FH of T2D.

  • 16.
    Lind, Lars
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Elmståhl, Sölve
    Fall, Tove
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    The metabolic profile of waist to hip ratio-A multi-cohort study2023In: PLOS ONE, E-ISSN 1932-6203, Vol. 18, no 2, article id e0282433Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The genetic background of general obesity and fat distribution is different, pointing to separate underlying physiology. Here, we searched for metabolites and lipoprotein particles associated with fat distribution, measured as waist/hip ratio adjusted for fat mass (WHRadjfatmass), and general adiposity measured as percentage fat mass.

    METHOD: The sex-stratified association of 791 metabolites detected by liquid chromatography-mass spectrometry (LC-MS) and 91 lipoprotein particles measured by nuclear magnetic spectroscopy (NMR) with WHRadjfatmass and fat mass were assessed using three population-based cohorts: EpiHealth (n = 2350) as discovery cohort, with PIVUS (n = 603) and POEM (n = 502) as replication cohorts.

    RESULTS: Of the 193 LC-MS-metabolites being associated with WHRadjfatmass in EpiHealth (false discovery rate (FDR) <5%), 52 were replicated in a meta-analysis of PIVUS and POEM. Nine metabolites, including ceramides, sphingomyelins or glycerophosphatidylcholines, were inversely associated with WHRadjfatmass in both sexes. Two of the sphingomyelins (d18:2/24:1, d18:1/24:2 and d18:2/24:2) were not associated with fat mass (p>0.50). Out of 91, 82 lipoprotein particles were associated with WHRadjfatmass in EpiHealth and 42 were replicated. Fourteen of those were associated in both sexes and belonged to very-large or large HDL particles, all being inversely associated with both WHRadjfatmass and fat mass.

    CONCLUSION: Two sphingomyelins were inversely linked to body fat distribution in both men and women without being associated with fat mass, while very-large and large HDL particles were inversely associated with both fat distribution and fat mass. If these metabolites represent a link between an impaired fat distribution and cardiometabolic diseases remains to be established.

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  • 17.
    Marouli, Eirini
    et al.
    Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, London EC1M 6BQ, England;Queen Mary Univ London, Ctr Genom Hlth, Life Sci, London EC1M 6BQ, England.
    Del Greco, M. Fabiola
    Univ Lubeck, Inst Biomed, Eurac Res, Affiliated Inst, I-39100 Bolzano, Italy.
    Astley, Christina M.
    Boston Childrens Hosp, Boston, MA 02115 USA;Broad Inst MIT & Harvard, Cambridge, MA 02142 USA.
    Yang, Jian
    Univ Queensland, Inst Mol Biosci, Brisbane, Qld 4072, Australia;Univ Queensland, Queensland Brain Inst, Brisbane, Qld 4072, Australia.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Univ, Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA 02115 USA;Harvard Med Sch, Brigham & Womens Hosp, Dept Med, Div Prevent Med, Boston, MA 02215 USA.
    Berndt, Sonja, I
    NCI, Div Canc Epidemiol & Genet, NIH, Dept Hlth & Human Serv, Bethesda, MD 20892 USA.
    Caulfield, Mark J.
    Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, London EC1M 6BQ, England;Queen Mary Univ London, Barts Cardiovasc Biomed Res Ctr, Natl Inst Hlth Res, London EC1M 6BQ, England.
    Evangelou, Evangelos
    Imperial Coll London, Sch Publ Hlth, Dept Epidemiol & Biostat, London W2 1PG, England;Univ Ioannina, Dept Hyg & Epidemiol, Med Sch, Ioannina 45110, Greece.
    McKnight, Barbara
    Univ Washington, Dept Biostat, Seattle, WA 98101 USA.
    Medina-Gomez, Carolina
    Erasmus MC, Dept Internal Med, NL-3015 GE Rotterdam, Netherlands;Erasmus MC, Dept Epidemiol, NL-3015 GE Rotterdam, Netherlands.
    van Vliet-Ostaptchouk, Jana V.
    Univ Groningen, Univ Med Ctr Groningen, Dept Endocrinol, NL-9713 GZ Groningen, Netherlands.
    Warren, Helen R.
    Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, London EC1M 6BQ, England;Queen Mary Univ London, Barts Cardiovasc Biomed Res Ctr, Natl Inst Hlth Res, London EC1M 6BQ, England.
    Zhu, Zhihong
    Univ Queensland, Inst Mol Biosci, Brisbane, Qld 4072, Australia.
    Hirschhorn, Joel N.
    Boston Childrens Hosp, Boston, MA 02115 USA;Broad Inst MIT & Harvard, Cambridge, MA 02142 USA.
    Loos, Ruth J. F.
    Icahn Sch Med Mt Sinai, Charles Bronfman Inst Personalized Med, New York, NY 10029 USA.
    Kutalik, Zoltan
    Lausanne Univ Hosp, Inst Social & Prevent Med, CH-1010 Lausanne, Switzerland;Swiss Inst Bioinformat, CH-1015 Lausanne, Switzerland.
    Deloukas, Panos
    Queen Mary Univ London, Barts & London Sch Med & Dent, William Harvey Res Inst, London EC1M 6BQ, England;Queen Mary Univ London, Ctr Genom Hlth, Life Sci, London EC1M 6BQ, England;King Abdulaziz Univ, Princess Al Jawhara Al Brahim Ctr Excellence Res, Jeddah 21589, Saudi Arabia.
    Mendelian randomisation analyses find pulmonary factors mediate the effect of height on coronary artery disease2019In: Communications Biology, E-ISSN 2399-3642, Vol. 2, article id 119Article in journal (Refereed)
    Abstract [en]

    There is evidence that lower height is associated with a higher risk of coronary artery disease (CAD) and increased risk of type 2 diabetes (T2D). It is not clear though whether these associations are causal, direct or mediated by other factors. Here we show that one standard deviation higher genetically determined height (similar to 6.5 cm) is causally associated with a 16% decrease in CAD risk (OR = 0.84, 95% CI 0.80-0.87). This causal association remains after performing sensitivity analyses relaxing pleiotropy assumptions. The causal effect of height on CAD risk is reduced by 1-3% after adjustment for potential mediators (lipids, blood pressure, glycaemic traits, body mass index, socio-economic status). In contrast, our data suggest that lung function (measured by forced expiratory volume [FEV1] and forced vital capacity [FVC]) is a mediator of the effect of height on CAD. We observe no direct causal effect of height on the risk of T2D.

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  • 18.
    Poveda, Alaitz
    et al.
    Lund Univ, Diabet Ctr, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmö, Sweden..
    Atabaki-Pasdar, Naeimeh
    Lund Univ, Diabet Ctr, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmö, Sweden..
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Brigham & Womens Hosp, Div Prevent Med, Boston, MA 02115 USA..
    Hallmans, Göran
    Umeå Univ, Sect Nutr Res, Dept Publ Hlth & Clin Med, Umeå, Sweden..
    Renström, Frida
    Lund Univ, Diabet Ctr, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmö, Sweden.;Umeå Univ, Sect Nutr Res, Dept Publ Hlth & Clin Med, Umeå, Sweden.;Cantonal Hosp St Gallen, Div Endocrinol & Diabet, St Gallen, Switzerland..
    Franks, Paul W.
    Lund Univ, Diabet Ctr, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmö, Sweden.;Umeå Univ, Sect Nutr Res, Dept Publ Hlth & Clin Med, Umeå, Sweden.;Harvard Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA..
    Association of Established Blood Pressure Loci With 10-Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension2020In: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, E-ISSN 2047-9980, Vol. 9, no 16, article id e014513Article in journal (Refereed)
    Abstract [en]

    Background Genome-wide association studies have identified >1000 genetic variants cross-sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure-associated variants with long-term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population. Methods and Results We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRS(SBP)): 554 variants; diastolic blood pressure GRS (GRS(DBP)): 481 variants; mean arterial pressure GRS (GRS(MAP)): 20 variants; pulse pressure GRS (GRS(PP)): 478 variants; hypertension GRS (GRS(HTN)): 22 variants; combined GRS (GRS(com)(b)): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRS(comb) was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.101.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.991.25) while controlling for traditional risk factors. The addition of GRS(comb) to a model containing traditional risk factors only marginally improved discrimination (Delta area under the ROC curve = 0.001-0.002). Conclusions GRSs based on discovered blood pressure-associated variants are associated with long-term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.

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  • 19.
    Rukh, Gull
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Brigham & Womens Hosp, Harvard Med Sch, Prevent Med Div, Boston, MA USA..
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cardiology.
    Schioth, Helgi Birgir
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences.
    Evidence of a Causal Link Between the Well-Being Spectrum and the Risk of Myocardial Infarction: A Mendelian Randomization Study2022In: Frontiers in Genetics, E-ISSN 1664-8021, Vol. 13, article id 842223Article in journal (Refereed)
    Abstract [en]

    Epidemiological studies have provided extensive evidence regarding the role of psychological risk factors in the pathogenesis of cardiovascular disease (CVD), but whether these associations are causal in nature is still unknown. We aimed to investigate whether the association between the wellbeing spectrum (WBS; derived from four psychological traits including life satisfaction, positive affect, neuroticism, and depressive symptoms) and CVD risk is causal. By employing a two-sample Mendelian randomization (MR) approach, the effect of the WBS on four CVD outcomes, including atrial fibrillation, heart failure, myocardial infarction, and ischemic stroke, was investigated. The genetically predicted WBS was associated with 38% lower risk for heart failure (odds ratio (OR): 0.62; 95% confidence interval [CI]: 0.50-0.78; P: 2.2 x 10(-5)) and 40% reduced risk of myocardial infarction (OR: 0.60; 95% CI: 0.47-0.78; P: 1.1 x 10(-4)). Of the WBS constituent traits, only depressive symptoms showed a positive causal association with heart failure and myocardial infarction. Neither WBS nor WBS constituent traits were associated with atrial fibrillation and ischemic stroke. In multivariable MR analyses, when genetic instruments for traditional CVD risk factors were also taken into consideration, the WBS was causally associated with a reduced risk for heart failure (OR: 0.72; 95% CI: 0.58-0.88; P: 0.001) and myocardial infarction (OR: 0.67; 95% CI: 0.52-0.86; P: 0.002). This study provides evidence that a higher WBS is causally associated with a decreased risk of developing CVD and, more specifically, myocardial infarction; moreover, the association is mainly driven by depressive symptoms. These results support current guidelines that suggest improving psychological wellbeing may help in reducing the burden of cardiovascular disease.

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  • 20.
    Sayols-Baixeras, Sergi
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. CIBER Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain .
    Dekkers, Koen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Baldanzi, Gabriel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jönsson, Daniel
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lin, Yi-Ting
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cardiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology. Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden .
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Preventive Medicine Division, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA.
    Nguyen, Diem
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Varotsis, Georgios
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Pita, Sara
    Nielsen, Nynne
    Eklund, Aron C
    Holm, Jacob B
    Nielsen, H Bjørn
    Ericson, Ulrika
    Brunkwall, Louise
    Ottosson, Filip
    Larsson, Anna
    Ericson, Dan
    Klinge, Björn
    Nilsson, Peter M
    Malinovschi, Andrei
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology, Integrative Physiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Physiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Lung- allergy- and sleep research.
    Lind, Lars
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Bergström, Göran
    Sundström, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Ärnlöv, Johan
    Engström, Gunnar
    Smith, J Gustav
    Orho-Melander, Marju
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Streptococcus Species Abundance in the Gut Is Linked to Subclinical Coronary Atherosclerosis in 8973 Participants From the SCAPIS Cohort2023In: Circulation, ISSN 0009-7322, E-ISSN 1524-4539, Vol. 148, no 6, p. 459-472Article in journal (Refereed)
    Abstract [en]

    Background: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography-based measures of coronary atherosclerosis and to explore relevant clinical correlates.

    Methods: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of stool, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva.

    Results: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10-5). Associations were largely similar across coronary computed tomography angiography-based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. Five species, including 3 streptococci, correlated with the same species in saliva and were associated with worse dental health in the Malmö Offspring Dental Study. Microbial functional potential of dissimilatory nitrate reduction, anaerobic fatty acid β-oxidation, and amino acid degradation were associated with coronary artery calcium score.

    Conclusions: This study provides evidence of an association of a gut microbiota composition characterized by increased abundance of Streptococcus spp and other species commonly found in the oral cavity with coronary atherosclerosis and systemic inflammation markers. Further longitudinal and experimental studies are warranted to explore the potential implications of a bacterial component in atherogenesis.

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  • 21.
    Visvanathar, Robin
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Censin, Jenny
    Menzel, Uwe
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Palaeobiology.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Geriatrics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Genetic Variation and Sex-Stratified Advanced Body Composition Analysis: Neck-to-Knee MRI and Genetics in the UK BiobankManuscript (preprint) (Other academic)
    Abstract [en]

    Background The heritability of body composition has been studied extensively by researchers. However, few studies have explored the genetic variation of advanced body composition phenotypes derived from magnetic resonance imaging (MRI). In this study, polygenic risk scores (PRS) and single nucleotide polymorphisms (SNPs) that are associated with image-derived features from water- and fat separated MRI are reported. Method and materials The analysis was performed with the image processing framework Imiomics to attain spatial normalisation of large imaging cohorts from the UK Biobank. The study included 13,300 men and 13,849 women following GWAS and image data quality controls. Imiomics was further applied to generate voxel-wise Pearson correlation coefficient volumes. Relative effect sizes from six SNPs (rs1358980-T, rs1936805-T, rs2820443-C, rs6567160-C, rs10195252-C and rs13021737-G) were examined for associations with segmented tissue volumes and tissue fat fractions. In addition, the LDpred-derived PRS were compared with genome-wide significant only derived PRS for body mass index (BMI), waist-to-hip ratio (WHR) and height. Results Imiomics and GWAS integration delivered a detailed mapping of individual SNPs to the tissue volume and fat fraction of regional adipose tissue depots, heart, liver, lungs and thigh muscle. A putatively less harmful relationship between gluteofemoral SAT and the two obesity-related SNPs, rs6567160-C and rs1936805-T, compared with other tissues was found. The genetic variant, rs1358980-T, located upstream of VEGFA, was the highest ranked SNP inversely associated with gluteofemoral SAT volume in both sexes (r= -0.0245, p<0.05 and r= -0.0257, p<0.05 in men and women, respectively). Observed effect sizes were overall higher with LDpred-derived PRS compared with genome-wide significant only scores. Conclusion An image-based exploratory integration approach guided by Imiomics enabled efficient and large-scale analysis of advanced body composition and genetic variation.  

  • 22.
    Warensjö Lemming, Eva
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics.
    Byberg, Liisa
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics.
    Stattin, Karl
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics.
    Ahmad, Shafqat
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Harvard Med Sch, Prevent Med Div, Brigham & Womens Hosp, Boston, MA USA; Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Epidemiology.
    Elmståhl, Sölve
    Lund Univ, Dept Clin Sci, Div Geriatr Med, Lund, Sweden.
    Larsson, Susanna C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics. Karolinska Inst, Div Nutr Epidemiol, Inst Environm Med, Stockholm, Sweden.
    Wolk, Alicja
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics. Karolinska Inst, Div Nutr Epidemiol, Inst Environm Med, Stockholm, Sweden.
    Michaëlsson, Karl
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Orthopaedics.
    Dietary Pattern Specific Protein Biomarkers for Cardiovascular Disease: A Cross-Sectional Study in 2 Independent Cohorts2019In: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, E-ISSN 2047-9980, Vol. 8, no 11, article id e011860Article in journal (Refereed)
    Abstract [en]

    Background: Mechanisms related to the influence of diet on the development of cardiovascular disease are not entirely understood, and protein biomarkers may help to understand these pathways. Studies of biomarkers identified with multiplex proteomic methods and dietary patterns are largely lacking.

    Methods and Results: Dietary patterns were generated through principal component analysis in 2 population‐based Swedish cohorts, the EpiHealth (EpiHealth study; n=20 817 men and women) and the SMCC (Swedish Mammography Cohort Clinical [n=4650 women]). A set of 184 protein cardiovascular disease biomarkers were measured with 2 high‐throughput, multiplex immunoassays. Discovery and replication multivariable linear regression analyses were used to investigate the associations between the principal component analysis–generated dietary patterns and the cardiovascular disease–associated protein biomarkers, first in the EpiHealth (n=2240) and then in the Swedish Mammography Cohort Clinical. Four main dietary patterns were identified in the EpiHealth, and 3 patterns were identified in the Swedish Mammography Cohort Clinical. The healthy and the Western/traditional patterns were found in both cohorts. In the EpiHealth, 57 protein biomarkers were associated with 3 of the dietary patterns, and 41 of these associations were replicated in the Swedish Mammography Cohort Clinical, with effect estimates ranging from 0.057 to 0.083 (P‐value range, 5.0×10−2–1.4×10−9) for each SD increase in the relative protein concentration. Independent associations were established between dietary patterns and the 21 protein biomarkers. Two proteins, myeloperoxidase and resistin, were associated with both the healthy and the light meal pattern but in opposite directions.

    Conclusions: We have discovered and replicated independent associations between dietary patterns and 21 biomarkers linked to cardiovascular disease, which have a role in the pathways related to inflammation, endothelial and immune function, cell adhesion, and metabolism

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