Using Biomarkers to Measure Alcohol Use Sarah Cook London School of Hygiene & Tropical Medicine Using biomarkers in research on health workshop 20th February 2015

Alcohol Consumption Alcohol consumption is associated with many negative effects including physical, psychological and social problems Alcohol research needs valid measures of alcohol consumption

Measurement of Alcohol Consumption Population level data on sales, tax and production Self-reported from survey data Volume of ethanol Drinking pattern Drinking behaviours (e.g. drunkenness, hangover)

Self-reported volume of ethanol Quantity- Frequency Usual amount X Frequency X Drink strength (number of drinks) (drinking days) (ethanol content) Graduated- Frequency Recent recall

Problems with measuring alcohol Consumption Measurement error Difficult to remember Difficulty in calculating volumes What is a “Standard drink”? Shared containers Variation in strength of drinks Social desirability

Alcohol Biomarkers Using self-reported data on alcohol use is problematic More objective measures of alcohol use are needed Alcohol consumption has an effect on a wide range of biological parameters

Alcohol Biomarkers Blood Urine Hair Liver enzymes (GGT, AST, ALT) Carbohydrate deficient transferrin (CDT) High Density Lipoprotein cholesterol (HDL) Mean corpuscular volume (MCV) Urine 5-Hydroxtryptophol Hair Ethyl glucuronide

Liver Enzymes Gamma glutamyl transferase (GGT) Aspartate Transanimase (AST) Alanine Transanimase (ALT)

GGT Serum GGT is most commonly used alcohol biomarker Raised with chronic heavy drinking (on average 80-200g ethanol/day for several weeks) but this can be influenced by other factors (age, gender). More sensitive to alcohol than other liver enzymes but still generally low Not specific – raised by many other factors 10-25 UK alcohol units/day

Carbohydrate Deficient Transferrin (CDT) Variant of serum glycoprotein transferrin produced in the liver Increased with chronic heavy drinking (60-80g ethanol daily over at least 2 weeks) Several factors effect relationship between alcohol and CDT e.g. gender, smoking, body mass index More specific than GGT but similar sensitivity Not strongly correlated wit GGT so they could be used in combination. Not raised in non alcoholic liver disease but raised with primary biliary cirrhosis, chronic acute hepatitis, severely decompensated liver disease

Limitations of alcohol biomarkers There are lots of potential alcohol biomarkers but no gold standard measure has been found Sensitivity and specificity generally low Only raised with heavy, sustained drinking Relationship between alcohol intake and biomarker may be influenced by other factors (interactions) Difficult to interpret raised levels in terms of actual volume consumed, drinking pattern

Are alcohol biomarkers useful?

Association between alcohol use and cardiovascular risk factors in Russian Men: An Example of the Use of Alcohol Biomarkers

Study Design Data from the Izhevsk Family Study Cross-sectional survey of men aged 25-60 living in the city of Izhevsk, Russia (2008-9) Men and a proxy completed a questionnaire which included very detailed questions on alcohol consumption Attended a health check which included a blood test Sample size N=978 men

Outcome: Cardiovascular risk factors Hypertension (binary) Serum lipids High density lipoprotein cholesterol (mmol/litres) Low Density lipoprotein cholesterol (mmol/litres) Hypertension mean SBP>139mm hg or mean DBP>89 mm Hg or taking prescribed anti-hypertensive medication

Alcohol measures: self-reported spirit intake Usual volume of spirits 0.76 1.00 Spirit Intake Maximum volume of spirits 0.49 Frequency of drinking spirits

Alcohol measures- proxy reported acute dysfunctional drinking Frequency of hangover 0.84 0.93 Frequency of excessive drunkenness Acute alcohol-related dysfunction 0.84 Frequency of sleeping in clothes because of drunkenness 0.85 Frequency of failing family or personal obligations because of drinking

Alcohol measures- alcohol biomarkers Log Gamma-glutamyl transferase (GGT) Log Carbohydrate Deficient Transferrin (CDT)

Alcohol and Hypertension

Adjusted for age,education, level of amenities, marital status, employment status, smoking, physical activity and body mass index Ors for continuous variables Adjusted for age, education, level of amenities, marital status, employment status, smoking, physical activity and body mass index

Alcohol and Hypertension Alcohol Use Measure Odds ratio* (95% CI) Spirit intake 1.27 (1.08, 1.49) Acute alcohol-related dysfunction 1.33 (1.14, 1.56) GGT 2.26 (1.79, 2.87) CDT 1.74 (1.43, 2.13) Odds ratios refer to change per unit increase in latent variables/biomarkers *Adjusted for age, education, level of amenities, marital status, employment status, smoking, physical activity and body mass index

Alcohol use and HDL-C

Alcohol and HDL Alcohol Use Measure Coefficient* (95% CI) Spirit intake 0.18 (0.15, 0.20) Acute alcohol-related dysfunction 0.16 (0.13, 0.19) GGT 0.20 (0.18, 0.23) CDT 0.31 (0.29, 0.33) *Adjusted for age, education, level of amenities, marital status, employment status, smoking, physical activity and body mass index

Alcohol Use and LDL-C

Alcohol and LDL-C Alcohol Use Measure Coefficient* (95% CI) Spirit intake -0.11 (-0.17, -0.05) Acute alcohol-related dysfunction -0.12 (-0.19, -0.06) GGT 0.04 (-0.02, 0.11) CDT -0.16 (-0.23, -0.08) *Adjusted for age, education, level of amenities, marital status, employment status, smoking, physical activity and body mass index

Why does GGT look different? GGT is raised for many reasons (not just alcohol) These include age, obesity, smoking, use of certain medications, non alcoholic liver disease and diabetes GGT associated with cardiovascular disease even in non-drinkers Is it an appropriate biomarker for the question?

Conclusions Alcohol biomarkers are not a simple solution to the issues of how to measure alcohol use BUT they can be useful alongside data on alcohol use from other sources to improve overall picture/provide validation Caution is needed when your biomarker is raised for many reasons as you may see associations not due to the factor of interest The best way to use biomarkers in alcohol research is still a question to explore

Acknowledgements David Leon Bianca De Stavola