Bhramar Mukherjee, PhDProfessor of Biostatistics and Epidemiology

University of Michigan School of Public Healthbhramar@umich.edu

SAMSI-SAVI Workshop, Mumbai, 2016Working Group # 6

Elena Colicino Sudha Ramalingam

Working Group 6: Epigenomics

Bhramar Mukherjee

The Patriotic Peacocks

Bhramar

Tanujit

Rajani

Prakash

Mohan

Dimple

Sharayu

What is interaction?

Why measure it?

-biology, sub-group identification, improving power

How to measure it?

-Choice of scale, method of analysis, coding

When to report it?

-public health relevance, biological significance, statistical significance

Introduction

Interactions

“Interaction as statisticians think of it is a Weasel

parameter.” –Professor David Clayton, JSM 2012

Weasel Word: “an informal term for words and phrases aimed at creating an impression that a specific and/or meaningful statement has been made, when only a vague or ambiguous claim has been communicated, enabling the specific meaning to be denied if the statement is challenged” (wikipedia)

Statistical Interaction

Very few replicable interactions reported in human observational studies!

Me, 1978

Me, 2016

Gene x Environment x Time

Lead exposure among children in

India: determinants, neurobehavioral

effects and genetic susceptibility

Working Group 6: Data Example

Environmental Health Perspective, 2011

Dataset

Neurotoxicology, 2013

Dataset

World blood lead levels among

children

Burden of disease, 2010

Lead levels and lead in gasoline

USA, NHANES II

( Annest et al. 1983)

Sources of lead exposure

Leaded gasoline phased later than in US

Leaded paint

Occupational:• Garage workers

• Smelting and metal working operations

• Jewelery workers

• Industrial activity

• Mining

Cultural practices • Ayurvedic medication

• Cosmetics (surma, sindhur)

• Holi colors

• Spices

Cosmetics

Religious

powders

Ayurvedic medication

Lead in paint (2009)

Clark, C.S. et al, Lead levels in new enamel household paints from Asia, Africa and

South America. Environ. Res. (2009), doi:10.1016/j.envres.2009.07.002.

Lead Paint

New York Times 2007NDTV 2010

Electronic waste

10-20,000 tonnes, employing 25,000 people, in New Delhi alone

E waste management and handling Rule 2011 ( new law MOEF, India) Needs implementation

Toxics link 2010

Determinants of blood lead levels among 3-7 year old children in Chennai, India (2005-2006)

India Lead Study (Chennai)

Study population (N= 756)• Cross-sectional• 12 schools (3 in 4 zones)• 3-7 year old children

High

industry

Low

Industry

High

traffic

HT/HI

(3 schools)

HT/LI

(3 schools)

Low

traffic

LT/HI

(3 schools)

LT/LI

(3 schools)

Chennai

• Blood lead levels assessed by• LeadCare™ Analyzer

1 . 5 4 . 5 7 . 5 1 0 . 5 1 3 . 5 1 6 . 5 1 9 . 5 2 2 . 5 2 5 . 5 2 8 . 5 3 1 . 5 3 4 . 5 3 7 . 5 4 0 . 5

0

5

1 0

1 5

2 0

2 5

3 0

P

e

r

c

e

n

t

BL LDistribution of blood lead levels (g/dl) in children in

Chennai

N=756

Mean=11.5 g/dl

Range=2.6-40.5 g/dl

55% > 10 µg/dl

2% > 10 µg/dl (NHANES III)

Assessment of Predictors

Questionnaires (primary care givers : Tamil)

• Socioeconomic statuso Family income, parental education, occupationo Type of house

• Possible sources of exposureo Residence (traffic and industry zone), parental occupation, presence of

lead based industry, traffic level near houseo Type of painto Sources and storage of drinking watero Surma and ayurvedic medication use

Predictors of blood lead

Variables Estimate 95% CI Partial R2 **

Age (months) 0.002 -0.001 0.005 0.003

Sex -0.028 -0.094 0.039 0.001

Average monthly family income (Rs)***

<2000 0.259 0.125 0.394 0.028

2000-4000 0.233 0.123 0.342 0.033

4000-6500 0.182 0.081 0.282 0.017

Drinking water storage vessel***

Brass/ Bronze 0.210 0.061 0.359 0.010

Residence ***

High industry 0.074 -0.082 0.231 0.007

* accounting for clustering at school level using generalized estimating equations

** unadjusted for clustering using linear regression

*** compared to >6500 Rs/ month, ** all other drinking water storage vessels, ***low industry area

Total model R2= 5.8%

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

<2000

2000-4000

4000-6500

>6500

Bra

ss/B

ronze

Oth

er

Income (Rs) DWV

Od

ds r

atio

(>10µg/dl)

DWV: Type of vessel used for storage of drinking water.

Adjusted for age (months), sex

p-values<0.05

Conclusions

• Blood lead levelso Lower socioeconomic statuso Drinking water stored in brass or bronze vessels

Residence in a high industry zone (<5 year old)

• No effect of use of ayurvedic medication, surma, traffic, paint

• Little variation in blood lead was explainedo Need in depth exposure assessment

Predictors of blood lead

Lead exposure and behavior,

IQ, Visual Motor skills children

in Chennai, India

Lanphear et al. 2005

Lead and IQ

o IQ is best characterized

• (Needleman 1979, Bellinger 1983)

o No threshold

o Non-linear dose-response

• (Schwartz 1994)

Heated debate!!

Lanphear et al 2005

Behavioral and cognitive assessmentBehavior: Questionnaires administered to the class teachers

Connors ADHD DSM IV Scales (CADS)o ADHD Indexo DSM IV: Hyperactivityo DSM IV: Inattention

Behavior Rating Inventory of Executive Function (BRIEF)o Executive function compositeo Behavioral regulation (inhibit, shift, emotional control)o Metacognition (Initiate, working memory, planning, organization of materials,

monitoring)

Connors Teacher Rating Scales (CTRS-39)o Anxiety, Sociability, (Aggression, Hyperactivity, Inattention)

Behavioral and cognitive assessment (con’t)Intelligence

• Binet - Kamat Intelligence scales ( Tamil)o mental age/ chronological age= IQo administered to children

Genotyping

• Bioserve Hyderabad, India• Mass Array Iplex (Sequenom process)

o PCR and mass spectrometryo Blood

• Negative and positive controls o 24 DNA samples from the Coriell Discovery panel

Effect of lead and hemoglobin (Hb) on IQGeneralized estimating equations*

Roy et al pending publication

Lead and Visual motor skills

Pallaniapan & Roy et al 2011

ConclusionsLead and behavior

• Blood lead levels are associated with poorer behavior and visual-motor skillso ADHD, internalizing behaviors and executive function

• Executive function is most sensitive to lead (0.4 SD)

o 4 IQ points (0.25 SD IQ)o In ADHD, inattention is most affectedo No effect seen on hyperactivity

• Dose-response relationships are linear for behavior

• Blood lead levels are associated with poorer

Lead exposure, iron and

intelligence: genetic

susceptibility

Lead and IQ

Wide variation in effect estimates

• Residual confounding

• Measurement error

• Different dose ranges

• Effect modification

• Nutritional differences

• Genetic differences

Lanphear et al. 2005

Effect modification by

Transferrin C2 polymorphsim

Effect modification by

Transferrin C2 polymorphsim

Roy et al Pending publication

Distribution of DRD2 Taq IA genotype

Effect of lead and Hb on IQ by DRD2 genotype

Roy et al

2011

Hemoglobin, Lead & IQ: genetic susceptibility

-

--

--

-* * * *

IQIQ

Data consists of 159 variables, including genotype data on 18 genetic polymorphisms

We will try to reproduce the published analysis with one marker at a time:

-Choice of confounders

-Transformation of Y and X

-Dose response relationship

-Interpreting interaction on the transformed scale

-Reporting of findings

-How robust are the conclusions

-Extend to incorporate multiple markers, calculate a polygenic risk score.

-Unexplored Associations (birth order related to IQ?)

Plan for Analysis Working Group

Determinants Blood lead BehaviorADHDExecutive functionInternalizing behavior

CognitionIQ

Dopamine D2 receptor polymorphism

IronHemoglobin

SES

Industrial activity

Brass and bronze vessels

OVERARCHING PARADIGM

Transferrin C2 polymorphism

Research Team

Kalpana BalakrishnanKavitha PalaniapanPadmavathi RamaswamyVenkatesh S.M.Shankar K.M.

BIOSERVERama Modali

AKNOWLEDGEMENTS

David C. BellingerJoel SchwartzRobert WrightAnanya Roy

HSPHSRMC

Funding : NIH (R01 ES007821) , Fogarty grant (R03 TW005914)

University of TorontoHoward Hu

YSPHAdrienne Ettinger

Study Participants!

How do we translate all these findings of reported associations and

interactionsinto Public Health action?

Why Should Francesca care?