Harmonization Protocol / Microbiome in health and disease and in ageing

INTIMIC-KP Use Cases 3 and 4 (Microbiome in health and disease and in ageing, WP6)

INTIMIC-KP Use Cases 3 and 4 (Microbiome in health and disease and in ageing, WP6)

Networks -
Variables -
Approach
Prospective
Type
Qualitative
Procedures
Studies responsible for data processing
Participant Inclusion
Age range: 18+ years
Infrastructure
Data hosted in Opal servers on study site

Information Content

**Study question** “Differences in the microbiome composition between obese and non-obese adult individuals across different epidemiological studies” **Outcome variables** * Microbial alpha diversity assessed using the Shannon-Weiner diversity index (H’), which accounts for both the number of phylotypes (richness by means of ACE and Chao indices) and the proportion of the total accounted for by each phylotype (evenness) * Microbial beta diversity using the Bray-Curtis dissimilarity and Unweighted UniFrac. * Firmicutes to Bacteroidetes ratio (at phylum level) * Candidate list of bacteria identified in individual stool samples (at Phylum and Genus level) (see Table A3 in appendix). * Enterotype determination (high-level classification of microbiome compositional states) **Exposure variables** 1. Anthropometric measurements: Height, Weight, Waist Circumference: * Obesity defined by body mass index (BMI) ≥30 kg/m2 (as compared to non-obesity, BMI <30 kg/m2). Or: * Abdominal obesity based on waist circumference ≥102 cm in men and ≥88 cm in women, or waist-to-hip ratio ≥0.95 in men and ≥0.80 in women (as compared to non-obesity based on waist circumference <102 cm in men and <88 cm in women, or waist-to-hip ratio <0.95 in men and <0.80 in women). * Overweight defined by BMI ≥ 25 kg/m2 (as compared to non-overweight (BMI<25 kg/m2) 2. Dietary intake (see **Table 1**): Healthy Eating Index (HEI-2015): the HEI-2015 consists of 13 food items. The first 6 items include (1) **total vegetables**; (2) **total fruits**; (3) **whole fruits**; (4) **greens and beans**; (5) **seafood and plant proteins**; and (6) **total proteins**, which can be scored from 0 to 5 points each. The remaining 7 items include (7) **whole grains**; (8) **low-fat dairy**; (9) **fatty acids ratio** (polyunsaturated fatty acids plus monounsaturated fatty acids to saturated fatty acids); (10) **refined grains**; (11) **sodium**; (12) **added sugars**; and (13) **saturated fats**, which can be scored from 0 to 10 points each. Most food components (except for fatty acids ratio, added sugars, and saturated fats) are scored on a density basis per 1000 kcal or as a percentage of energy. Four components (sodium, refined grains, added sugars, and saturated fats) are reverse scored (i.e., higher intakes receive lower scores). Total HEI-2015 scores are computed by aggregating scores across individual dietary components such that total scores ranged from zero (poor diet quality) to 100 (optimal diet quality). Because HEI-2015 does not include a specific component for alcohol, we should run additional sub-analyses adjusting for alcohol intake **Table 1. List of dietary intake variables** | Nutrients Intake | Units | | -------- | -------- | | Total energy intake | Kcal/day| |Total Protein | % of TE | |Plant proteins |% of TE | |Total fat | % of TE | |Saturated fat | % of TE| |Polyunsaturated fat | % of TE| |Monounsaturated fats | % of TE| |Carbohydrates | % of TE| |Total Sugar | % of TE| |Alcohol | % of TE or g/day| |Dietary fibre | g/day| |Salt | g/day| |Sodium | g/day| |**Food group intake** | | |Total fruits | g/day | |Whole fruits | g/day | |Total vegetables | g/day | |Whole grains | g/day | |Refined grains| g/day | |White meat | g/day | |Red meat | g/day | |Fish and Seafood | g/day | |Dairy | g/day | |Fruit juice | g/day | |Processed meat | g/day | |Sugar sweetened carbonated drinks | g/day | |Sweets and pastries | g/day | |Nuts | g/day | TE: total Energy. Taken from (Celis-Morales 2019) with amendments. **Covariates** * Sociodemographic: Age, sex, education, smoking * Related with BMI and microbiome: cardiometabolic diseases, physical activity, energy intake, alcohol intake * Confounding microbiome composition: current medication, current use of antibiotics (or use of antibiotics in the past year), regular use of probiotics * Study source (to account for technical and data processing issues) * Related to collection and measurement of microbiome data: DNA extraction kit, gene region, sequencing platform used

Additional Information

**Study inclusion criteria** 1. Study design: Cross-sectional data from either cross-sectional or cohort (baseline or single follow-up data) or case-control (controls only) or intervention study (control arm) 2. Mandatory data: Data on microbiome and anthropometric measurements (to address the primary aim) 3. Additional data: dietary intake (to address the secondary aim) 4. Age range: 18+ years

Studies Included

Study Population Data Collection Event
EPIC-Potsdam EPIC-Potsdam EPIC-DZD
DONALD Study DONALD DONALD
NU-AGE Italian_cohort elderly-microbiome-study-_italian-cohort-from-nu-age
ErNst ernst ernst
FoCus focus FoCus_baseline
MeaTIc meatic meatic
MetaCardis MetaCardis population metacardis
Diet4MicroGut diet4microgut diet4microgut

Initiatives Included

Harmonization

Complete - study-specific variable is the same as DataSchema variable (status = identical) or needs transformation to generate DataSchema variable (status = compatible)
Partial - categorical study-specific variable (status = proximate) or other types (status = tentative) could generate DataSchema variable but with loss of information
Impossible - study does not collect DataSchema variable (status = unavailable) or cannot be used to generate DataSchema variable (status = incompatible)
Undetermined - harmonization status not determined
Not Applicable - harmonization status is not relevant
Variable EPIC-Potsdam DONALD Study NU-AGE ErNst FoCus MeaTIc MetaCardis Diet4MicroGut