Using Pre-clinical Biomarkers and Epidemiological Methods ... seminar.pdf · Using Pre-clinical...
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Using Pre-clinical Biomarkers and Epidemiological Methods to Assess
the Effects of Cannabinoids on Disease
Omayma Alshaarawy, MBBS, PhDResearch Associate
Department of Epidemiology and BiostatisticsMichigan State University
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Frequency of Marijuana Use
Insulin HOMA-IR Glucose Hemoglobin A1c
Age, sex adjustedNeverPast use −14.0% (−19.0%, −8.7%) −16.3% (−21.8%, −10.3%) −3.69 (−5.85, −1.53) −0.13 (−0.20, −0.06)
Current use −27.6% (−33.7%, −21.0%) −28.8% (−35.0%, −22.0%) −2.34 (−4.64, −0.03) −0.08 (−0.18, −0.01)
Multivariable adjusted
NeverPast use −5.5% (−11.5%, 1.0%) −7.0% (−13.5%, 0.1%) −2.10 (−4.24, 0.03) −0.07 (−0.16, 0.03)
Current use −14.9% (−23.1%, −5.7%) −15.4% (−23.9%, −5.9%) −0.94 (−3.10, 1.21) −0.01 (−0.14, 0.12)
Multivariable adjusted, with BMI
NeverPast use −5.3% (−11.2%, 0.9%) −6.9% (−13.1%, −0.2%) −2.16 (−4.22, −0.11) −0.07 (−0.17, 0.02)
Current use −11.8% (−19.0%, −3.9%) −12.0% (−19.4%, −4.0%) −0.47 (−2.51, −1.57) 0.02 (−0.11, 0.15)
Multivariable adjusted, excluding diabetic persons
NeverPast use −7.1% (−13.1%, −0.6%) −7.7% (−14.1%, −0.8%) −0.62 (−1.42, 0.19) −0.01 (−0.05, 0.02)
Current use −17.6% (−27.4%, −6.6%) −18.2% (−27.9%, −7.0%) −0.64 (−1.74, 0.47) −0.04 (−0.09, 0.02)
Penner et al. The Impact of Marijuana Use on Glucose, Insulin, and Insulin Resistance among US Adults, The American Journal of Medicine 2013.
Adjusted Mean/Percent Differences in Measures of Carbohydrate Metabolism and Body Mass Index According to Marijuana Use Among Participants From the National Health and Nutrition Examination Survey, 2005 to 2010
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Smit & Crespo. Dietary intake and nutritional status of US adult marijuana users: results from the Third National Health and Nutrition Examination Survey. Public Health Nutrition 2001.
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Rodondi et al. Marijuana Use, Diet, Body Mass Index, and Cardiovascular Risk Factors (from the CARDIA Study), The American Journal of Cardiology 2006.
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Characteristics Marijuana Use Over 15-Year Study Period p Value
Never User <180 Days 180–1,799 Days
≥1800 Days
(n = 2,252) (n = 610) (n = 601) (n = 154)Dietary factors
Daily caloric intake (kcal/d) 2,746 2,884 3,428 3,365 <0.001
Saturated fat (% daily calories) 13.2 13.3 13.1 13.3 0.89
Unsaturated fat (% daily calories) 23.3 23.5 23.3 23.1 0.37
Carbohydrates (% daily calories) 48.5 46.8 46.5 45.6 <0.001
Protein (% daily calories) 14.6 14.4 14.6 14.2 0.04
Adjusted mean values of dietary factors according to average marijuana use from 1985 to 2000 in the CARDIA study
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Cannabis and Body Weight
Hayatbakhsh et al. Cannabis use and obesity and young adults. American Journal of Drug and Alcohol Abuse 2010.
Le Strat & Le Foll. Obesity and Cannabis Use: Results From 2 Representative National Surveys. American Journal of Epidemiology 2011.
Beulaygue et al. Got Munchies? Estimating the Relationship between Marijuana Use and Body Mass Index. The Journal of Mental Health Policy and Economics 2016.
Li et al. Associations Between Body Weight Status and Substance Use Among African American Women in Baltimore, Maryland: The CHAT Study. Substance Use Misuse 2016.
Sabia et al. The Effect of Medical Marijuana Laws on Body Weight. Health Economics 2017.
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The National Health and Nutrition Examination Survey (NHANES)
The National Surveyson Drug Use and Health (NSDUH)
Years 2005-2012 =Target population Nationally representative
of the non-institutionalized US civilian population.
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Sampling The sample employs an independent, multistage area probability sample for each State and the District of Columbia.
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Cannabis and Diabetes Mellitus
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The National Health and Nutrition Examination Survey (NHANES)
The National Surveyson Drug Use and Health (NSDUH)
Exposure of interest (cannabis use)
The drug use questionnaire was administered using the Audio Computer Assisted Self Interview system (ACASI).
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Participants were asked if they ever used
cannabis, age of first use, and if they used
cannabis in the past 30 days.
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Cannabis and Diabetes Mellitus
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The National Health and Nutrition Examination Survey (NHANES)
The National Surveys on Drug Use and Health (NSDUH)
Outcome of interest (diabetes mellitus)
•Self-reported physician-diagnosis•Current use of oral hypoglycemic medication or insulin•Glycosylated hemoglobin level (HbA1c) ≥ 6.5%
• Self-reported physician-diagnosis.
Statistical analysis •Multivariable-adjusted logistic regression•Weighting and variance estimation appropriate forcomplex survey data•STATA, version 13
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Cannabis and Diabetes Mellitus
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Cannabis and Diabetes Mellitus
Alshaarawy O and Anthony JC. Cannabis Smoking and Diabetes Mellitus: Results from Meta-analysis with Eight Independent Replication Samples. Epidemiology 2015.
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Meta-analysis summary OR
Survey
NSDUH 2009-10NHANES 2011-12
NHANES 2007-08NSDUH 2005-06
NSDUH 2011-12
NSDUH 2007-08
NHANES 2005-06
NHANES 2009-10
0.7 (0.6, 0.8)
Covariate adjusted OR(95% CI)
0.8 (0.5, 1.1)0.7 (0.4, 1.2)
0.4 (0.2, 0.7)0.7 (0.5, 0.9)
0.9 (0.6, 1.2)
0.5 (0.4, 0.7)
0.6 (0.3, 1.2)
0.9 (0.4, 2.1)
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Study-specific estimates that quantify the association linking diabetes mellitus and recently active cannabis use
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Cannabis use and Diabetes Mellitus
Alshaarawy O, Anthony JC. Cannabis Smoking and Diabetes Mellitus: Results from Meta-analysis with Eight Independent Replication Samples. Epidemiology 2015.
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Meta-analysis summary OR
NHANES 2007-08
NHANES 2011-12
NHANES 2009-10
NHANES 2005-06
Survey
0.7 (0.5, 0.97)
0.4 (0.2, 0.8)
0.8 (0.4, 1.4)
1.0 (0.4, 2.1)
0.8 (0.4, 1.5)
Additionally adjusted for BMI
OR (95% CI)
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The Cannabinoid System
Receptors (GPCR) CB1 CB2
Endocannabinoids Anandamide (AEA) 2-arachidonoylglycerol (2-AG)
Enzymes Fatty acid amide hydrolase (FAAH) Monoacylglycerol lipase (MAGL)
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CB1 receptors
Activation of CB1 receptors is responsible for the well-known appetite-inducing actions of cannabinoids (Kirkham et al. British Journal of Pharmacology 2002).
Activation of CB1 receptor promotes weight gain (Di Marzo. Diabetologia2008).
Rimonabant, a selective CB1 receptor inverse agonist has been shown to reduce body weight alongside improvements in other elements of the metabolic syndrome (Sam et al. Journal of Obesity 2011).
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Marijuana CB1
Food intakeWeight
Insulin resistance
Marijuana
Food intake
WeightInsulin resistance
CB1 receptors
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CB2 receptors
CB2 receptors participate in the regulation of cytokine release and function
CB2 activation is found to reduce TNFα, IL-2, IL-6, and IL-11; all elevated in diabetes and correlated to insulin resistance (Cabral & Griffin-Thomas. Expert Reviews in Molecular Medicine 2009, Calle & Fernandez. Diabetes Metabolism 2012).
The anti-inflammatory potential of CB2 activation was demonstrated in many inflammatory diseases in animal models (Croxford & Yamamura. Neuroimmunology 2005).
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Is the inverse association between cannabis use and diabetes mellitus due to the activation of CB2 receptors expressed
predominantly in the immune system?
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An acute phase reactant synthesized primarily by the liver, with levels increasing in response to injury, infection, or inflammation.
Circulating levels of CRP can be clinically useful in the prognosis/diagnosis of cardiovascular events and diabetes mellitus (Sattar & Hingorani. Diabetes 2009).
In NHANES, serum CRP has been quantified by latex-enhanced nephelometry.
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Cannabis and C- reactive protein
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Recently Active Cannabis use and Serum CRP (mg/L) LevelsData for the US Based on the National Health and Nutrition Examination 2005-2010
Alshaarawy O and Anthony JC. Cannabis smoking and serum C-reactive protein: A quantile regressions approach based on NHANES 2005-2010. Drug and Alcohol Dependence 2015.
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Limitations
NHANES and the NSDUH have an observational cross-sectional study design.
Cannabis use was self-reported.
There were no data on the route of administration, frequency of cannabis use beyond the 30 days prior to the interview, or potency of cannabis.
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Cannabis and Markers of Inflammation
We aim to add new epidemiological estimates to the cannabis-immunomodulatory body of research using the Coronary Artery Risk Development in Young Adults (CARDIA) study with 25 years of repeated measurements of cannabis use (Friedman et al. Journal of Clinical Epidemiology 1988).
The CARDIA study additionally provides measurement on:
Fibrinogen, an important component of the coagulation cascade, that has been associated with inflammation (Davalos and Akassoglou. Seminars in Immunopathology 2012).
Interleukin-6 (IL-6) a key cytokine produced by leukocytes as well as a variety of other cells, promoting B cells differentiation, expansion and activation of T cells, and the regulation of acute-phase responses (Schaper and Rose-John. Cytokine & Growth Factor Reviews 2015).
Alshaarawy O et al. Cannabis Use and Markers of Systemic Inflammation. The CARDIA Study. Under preparation21
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Cannabis and Markers of Inflammation
The CARDIA study was designed to measure risk factors for cardiovascular disease in a biracial (Black and White) cohort of 5115 women and men who underwent their initial exam in 1985-1986.
The study was designed to provide approximately equal representation across groups of age, sex, race, and education.
Community-based random sampling was performed in Birmingham, Chicago, and Minneapolis. In Oakland, respondents living in Oakland and Berkeley were randomly recruited from the Kaiser Permanente health plan membership.
Follow-up examinations occurred during 1987–1988 (Year 2), 1990–1991 (Year 5), 1992–1993 (Year 7), 1995–1996 (Year 10), 2000–2001 (Year 15), 2005–2006 (Year 20), and 2010-2011 (Year 25).
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Cannabis and Markers of Inflammation
The majority of participants have been examined at each follow-up (91%, 86%, 81%, 79%, 74%, 72% and 72% respectively).
Participants were asked to attend a morning examination after fasting for 12 hours and to avoid smoking and heavy physical activity for 30 minutes before the exam.
Outcomes:• Fibrinogen was measured at 3 exams (Y5, Y7 and Y20). • C-reactive protein was measured at 4 exams (Y7, Y15, Y20 and Y25).• IL-6 was measured in Y20.
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Cannabis and Markers of Inflammation
Cannabis use:
• A detailed, self-administered questionnaire based on items from the National Household Survey on Drug Abuse was administered at each exam.
• Ever users of cannabis were asked about the frequency of lifetime use (1-2 times, 3-9 times, 10-99 times and 100+ times).
• Recently active use was defined as cannabis use at least 1 day in the 30 days prior to the interview.
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Cannabis and Markers of Inflammation
The Generalized Estimating Equations modelling (GEE) developed by Liang and Zeger was then used to evaluate whether cannabis use might be associated with inflammatory biomarkers (Liang and Zeger. Biometrika 1986).
To investigate the impact of bias introduced by these losses to follow-up, we used inverse probability weighting (IPW).
Using data from all 8 exams, we then used multiple imputations to generate 10 complete datasets by replacing missing values of cannabis use and other covariates using sequential regression multivariate imputations (Azur et al. International journal of methods in psychiatric research 2011).
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Cannabis and Markers of Inflammation
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Y 5 Y 7 Y 2 0
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Cannabis and Markers of Inflammation
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Estimated relationship of baseline cannabis use (Y5) and plasma fibrinogen (mg/dl at Y5, Y7, Y20) levels, and baseline cannabis use (Y7) and CRP (mg/L at Y7, Y15, Y20, Y25) levels. CARDIA Study; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA
Recency of use Lifetime frequency of past useCannabis use Any past use Recent use 1-2 times 3-10 times 11-99 times 100+times
Panel A: Fibrinogen β (95%CI)
Crude -13 (-18, -8) -17 (-23, -11) 2 ( -6, 10) -13 (-19, -6) -13 (-19, -8) -20 (-25, -14)
Age-sex adjusted -12 (-17, -7) -10 (-15, -4) -1 (-8, 7) -13 (-19, -7) -14 (-20, -9) -13 (-18, -7)
Multivariable adjusted
-8 (-13, -3) -6 (-12, 0) 1 (-7, 8) -8 (-15, -2) -9 (-14, -4) -10 (-15, -4)
Additionally adjusted for BMI
-6 (-10, -2) -4 (-10, 2) -1 (-8, 5) -5 (-10, 1) -6 (-11, -1) -8 (-13, -3)
Panel B: ln (CRP) β (95%CI)
Crude -0.19 (-0.27, -0.10) -0.12 (-0.23, -0.01) -0.02 (-0.15, 0.12) -0.18 (-0.29, -0.06) -0.21 (-0.31, -0.11) -0.20 (-0.29, -0.11)
Age-sex adjusted -0.16 (-0.25, -0.08) -0.04 (-0.15, 0.07) -0.04 (-0.17, 0.10) -0.18 (-0.29, -0.06) -0.21 (-0.31, -0.11) -0.10 (-0.19, -0.01)
Multivariable adjusted
-0.11 (-0.20, -0.03) -0.01 (-0.13, 0.10) -0.02 (-0.15, 0.11) -0.11 (-0.22, 0.00) -0.14 (-0.24, -0.04) -0.09 (-0.19, 0.00)
Additionally adjusted for BMI
-0.07 (-0.15, <0.00) -0.01 (-0.11, 0.10) -0.04 (-0.15, 0.07) -0.06 (-0.16, 0.04) -0.09 (-0.18, <0.00) -0.06 (-0.14, 0.03)
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Estimated relationship of cannabis use (Y5, Y7, Y20) and fibrinogen levels (mg/dl at Y5, Y7, Y20), and cannabis use (Y7, Y15, Y20, Y25) and CRP levels (mg/L at Y7, Y15, Y20, Y25). CARDIA Study; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA
Recency of use Lifetime frequency of past useCannabis use Any past use Recent use 1-2 times 3-10 times 11-99 times 100+times
Panel A: Fibrinogenβ (95%CI)
Crude -11 (-16, -6) -15 (-20, -9) 0 (-8, 8) -9 (-16, -2) -12 (-18, -6) -18 (-23, -12)Age-sex adjusted -9 (-14, -4) -10 (-16, -4) -1 (-9, 6) -10 (-16, -3) -12 (-18, -7) -11 (-17, -6)Multivariable adjusted
-5 (-10, <0) -4 (-10, 2) 0 (-7, 8) -5 (-11, 2) -7 (-12, -1) -8 (-13, -2)
Additionally adjusted for BMI
-4 (-8, <0) -3 (-8, 2) -2 (-8, 5) -3 (-9, 2) -4 (-9, 0) -6 (-11, -1)
Panel B: ln (CRP) β (95%CI)
Crude -0.13 (-0.21, -0.04) -0.15 (-0.25, -0.06) -0.02 (-0.10, 0.01) -0.15 (-0.26, -0.03) -0.17 (-0.27, -0.07) -0.17 (-0.26, -0.08)
Age-sex adjusted -0.10 (-0.18, -0.02) -0.10 (-0.20, -0.01) 0.05 (-0.11, 0.13) -0.15 (-0.26, -0.04) -0.17 (-0.26, -0.07) -0.08 (-0.17, 0.01)
Multivariable adjusted
-0.06 (-0.14, 0.03) -0.06 (-0.16, 0.04) 0.02 (-0.10, 0.01) -0.09 (-0.20, 0.02) -0.10 (-0.20, 0.00) -0.05 (-0.15, 0.04)
Additionally adjusted for BMI
-0.02 (-0.09, 0.05) 0.00 (-0.09, 0.08) -0.01 (-0.11, 0.09) -0.04 (-0.13, 0.05) -0.02 (-0.10, 0.06) -0.01 (-0.08, 0.07)
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Future directions
Recruitment for Greater Lansing area Community Health Survey
The aim of the survey is to prospectively assess the health status of the Lansing community with research questions such as
• The immunomodulatory effects of cannabis
• The effect of the route of administration
• Collecting biological samples to measure different biomarkers
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Thank you
Funding sources: NCCIH K99-AT009156, NIDA T32DA021129
Acknowledgments : Prof. James Anthony, Prof Karl Olson (Olson lab), and Prof Norbert Kaminski (Kaminski lab)
The views expressed are those of the speaker and do not necessarily represent the views of the National Center for Complementary and Integrative Health, the National Institute of Drug Abuse, the National Institutes of Health; or Michigan State University.
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