for Psychiatric and

(1)

Anorexia Nervosa

Reconceptualized: Evidence for Psychiatric and

Metabolic Etiology

Cynthia Bulik, PhD, FAED

UNC Chapel Hill and Karolinska Institutet

(2)

Disclosures

• Shire Pharmaceuticals

– (grant recipient & advisory board)

• Pearson

– (author)

• Walker

– (author)

(3)

Gratitude

(4)

Anorexia Nervosa

A. Significantly low body weight

B. Intense fear of gaining weight or becoming fat C. Disturbance in the way in which one's body

weight or shape is experienced, undue influence of body weight or shape on self-evaluation, or persistent lack of recognition of the seriousness of the current low body weight.

Subtypes

Restricting: only caloric restriction and exercise Binge eating/purging: Binge eating and or purging

also present

(5)

Anorexia Nervosa: Mortality

• Highest mortality rate of any psychiatric disorder

• 5% per decade of follow-up

• Standardized mortality ratio 6.2-10.5

• Those with anorexia 10-50 times more likely to suicide than peers

• Third most common chronic illness

amongst adolescents

(6)

Treatment and Outcome

• Evidence base is weak (especially for adults)

• Relapse is common

• 20% chronicity

• High treatment dropout

• Family-based therapy (FBT) recommended for youth

• No effective medications

• Rapid re-loss of weight after therapeutic weight restoration

(7)

0 2 4 6 8 10 12 14 16 18 20

AN-R AN-BP ANBN BN BED PD No ED

Percent of Individuals with Suicide Attempts

Suicide Attempts Across ED Subtypes

Eating Disorder Subtype

% at te mp ts

PMID: 24364606

(8)

• Activity is more reinforcing than food

• Satiety is unpleasant

• Fats are aversive

• Acutely ill individuals with AN do not exhibit

“sickness behaviors”…until we renourish them!

• Bodies revert to a negative set point

What’s Intriguing About Anorexia Nervosa?

• Starvation is

reinforcing anxiolytic

euphorigenic

(9)

Paradoxical Response to Negative Energy Balance

Energy consumed

Exercise

Physical activity Rest

Fidgeting Purging

Energy expended

(10)

Genomics of AN

Family Studies:

Eating disorders run in families

Twin Studies:

Heritability of AN ~50-60%

Our discovery tools

have improved

(11)

GWAS: Workhorse of Genomic Discovery GWAS

Candidate Gene Association

• Cases versus Controls

• 1 or a few markers

• Prior knowledge/

guesswork essential

• Samples in the hundreds

GWAS

• Cases versus Controls

• ~1,000,000 genetic markers

• No prior knowledge;

no guesswork

• Samples in tens or hundreds of

thousands

(12)

Psychiatric Genomics Consortium (PGC)

https://www.med.unc.edu/pgc

> 800 Investigators

38 Countries 900,000 Samples

Open, Inclusive, Participatory, Democratic

(13)

Eating Disorders Working Group of the PGC

> 100 Investigators 20 Countries ~20,000 Samples

Co-Chairs

Bulik: UNC/KI Breen: KCL

2013

(14)

How to Read a Manhattan Plot

Chromosome Significance level

5 x 10 ^-8

(15)

Size Matters

(16)

Schizophrenia 2009

ISC 2009

3K cases

(17)

ISC 2009 3K cases

PGC1 9K cases

5 loci

(18)

PGC1 9K cases

5 loci

PGC1 + Sweden

14K cases

22 loci

(19)

PGC1 9K cases

5 loci

PGC1 + Sweden 14K cases 22 loci

PGC2

31K cases

78 loci

(20)

PGC1 9K cases

5 loci

PGC1 + Sweden 14K cases 22 loci

PGC2 31K cases 78 loci

2014

34K cases

45K controls

108 loci

(21)

ISC 2009 3K cases

PMID: 25056061

2014

34K cases

45K controls

108 loci

(22)

Anorexia Nervosa GWAS

Discovery:

2,907 AN cases

14,860 archived controls Replication:

2,677 AN cases

8,629 archived controls Japan Replication:

458 AN cases

421 archived controls 1,033 AN cases

3,733 controls

PMID: 21079607

PMID: 24514567

(23)

CHOP/Price 1,029 / 3,628

CHOP/Price + WTCCC3 3,495 / 10,982

WTCCC3

2,907 / 14,860

(24)

Anorexia GWAS July 2016

CHOP/Price + WTCCC3 3,495 / 10,982

1000 Genomes Phase 3

(25)

(26)

There’s Valuable Information Below

the Red Line!

(27)

LD Score Regression

• Estimates genetic correlations from published summary statistics

• Do not need to measure all of the traits on the same people

• Between diseases, “genetic analogue of comorbidity”

PMID: 25642630

(28)

Obesity

Schizophrenia

(29)

Brainstorm, Anttila et al (under review)

Anor exia

SCZ OCD

r _g =0.55

(30)

HDL cholesterol Phospholipids in large HDL Concentration of large HDL particles Total lipids in large HDL Cholesterol esters in large HDL Free cholesterol in large HDL Total cholesterol in large HDL Fasting glucose HOMA-Beta Fasting insulin HOMA-IR Hip circumference Obesity class 2 BMI BMI (Giant) Obesity class 1 Obesity class 3 Overweight Body fat percentage Extreme BMI College attended (SSGAC) Education years (SSGAC v2) Education years (SSGAC v1) Cross disorder (PGC v1) Schizophrenia (PGC v2) Schizophrenia (PGC v1) Neuroticism (SSGAC) Neuroticism

Neuroticism (GPC)

Personality Psychiatric Educational Weight & BMI

Insulin & glucose related Lipoprotein & cholesterol

-0.5 0.0 0.5

Genetic Correlation

Psychiatric

Cognitive performance Obesity, BMI,

Weight Glucose, HOMA-Beta Insulin

HDL measures

LDL measures Coronary

artery disease

- +

(31)

Neuroticism (GPC)

Personality Psychiatric Educational Weight & BMI

Insulin & glucose related Lipoprotein & cholesterol

-0.5 0.0 0.5

Genetic Correlation

Psychiatric Cognitive performance

Obesity, BMI, Weight

Glucose, HOMA-Beta Insulin

HDL measures

LDL measures Coronary

artery disease

- +

(32)

Neuroticism (GPC)

Personality Psychiatric Educational Weight & BMI

Insulin & glucose related Lipoprotein & cholesterol

-0.5 0.0 0.5

Genetic Correlation

Psychiatric Cognitive performance

Obesity, BMI, Weight

Glucose, HOMA-Beta

Insulin HDL measures

LDL measures Coronary

artery disease

- +

(33)

Neuroticism (GPC)

Personality Psychiatric Educational Weight & BMI

Insulin & glucose related Lipoprotein & cholesterol

-0.5 0.0 0.5

Genetic Correlation

Psychiatric Cognitive performance

Obesity, BMI, Weight

Glucose, HOMA- Beta Insulin

LDL measures Coronary

artery disease

- +

(34)

Psychiatric

Cognitive performance Obesity, BMI,

Weight

Glucose, HOMA-Beta Insulin

HDL measures

- +

Neuroticism (GPC)

Personality Psychiatric Educational Weight & BMI

Insulin & glucose related Lipoprotein & cholesterol

-0.5 0.0 0.5

Genetic Correlation

(35)

• (N=1,839)

• Random-coefficient growth models to describe premorbid BMI trajectories for

– anorexia nervosa (AN; N=261) – bulimia nervosa (BN; N=333)

– binge-eating disorder (BED; N=126) – purging disorder (PD; N=145)

– individuals without an ED (N=1,024)

(36)

Males Females

(37)

Reconceptualizing Anorexia Nervosa

• Uncanny ability to reach low BMI

• Frequent return to a “negative set point”

• Early divergence from BMI growth curves

• Negative correlations with BMI and other unhealthy metabolic parameters

• Positive correlations with healthy metabolic parameters

• Paradoxical reaction to negative energy balance

• Maintain low BMI even after recovery

(38)

Coming in 2017

(39)

ANGI successfully recruited 13,000 cases and 9,000 controls

in 3 years

(40)

~13,000 cases + controls

~5,000 cases + controls

Japan

South Korea

Germany

Netherlands

(41)

Next steps

Genotype all samples in the queue Meta-analyze

Identify biological pathways Determine functional significance of identified genes/pathways

Develop targeted therapeutics???

New hits?

(42)

ANGI +

Sweden

4,000 cases + controls

Denmark

5,000 cases + controls

Measured Genotypes Register Linkage Quality Registers

Riksät/Stepwise

+ +

= Unprecedented opportunity to model how GENES and

ENVIRONMENT act and co-act in eating disorders

(43)

The Intestinal

Microbiota in

Eating Disorders

(44)

(45)

A

Characterize Taxonomy and Diversity of Intestinal Microbiotas

AN T1

< 75% IBW

AN T2

~85% IBW

Healthy

Control

(46)

Demographic & Clinical Characteristics

Patients with AN (n=16)

Female 100%

Age 28.0 (11.7) years

BMI (admission) 16.2 (1.5) kg/m ²

BDI 26.6 (13.4)  moderate

BAI 17.7 (11.9)  moderate

EDE-Q (total) 3.6 (1.8) Dietary restraint 3.7 (1.9) Eating concern 3.4 (1.9) Shape concern 3.8 (1.9) Weight concern 3.4 (2.1)

Note: results are mean (± SD)

Exclusion criteria:

• Age <15 or >64 years

• History of GI surgery

• IBS, IBD, celiac

• Antibiotics/probiotics

in the last two months

(47)

Alpha (within sample) Diversity

Kleiman et al. (2015)

A diverse microbiota is a healthy microbiota!

Number of species present Chao-1

(Number & Relative Abundance)

(48)

Anorexia: Significant Association Between Depression and Bacterial Diversity

Higher BDI scores  lower bacterial diversity

PMID: 26428446

Depression,and eating disorder psychopathology associated with microbial

composition/diversity in patients with acute AN

(49)

Normal

Microbiota Germ-free

Gnotobiotics

gnostos 'known'

bios 'life'

(50)

Percent time spent in the center of the open field in GF mice and GF mice colonized with HC or AN.

Open Field Test

Increased Anxiety in Germ-free Mice

More time in open space =

less anxious

(51)

Limitations

• Limited power at the lowest taxonomic levels

• 16S rRNA data describes microbial composition/diversity but not

metabolic activity or functional impact

• Did not control for dietary intake

• Unable to compare patients with AN to similarly malnourished

individuals without AN

(52)

Integration

Genomics

Microbiome Phenotype/

Behavior

(53)

ANGI ++

Influence of host genomics on intestinal microbiota in AN

5-site microbiota sampling US, Sweden, Australia, NZ

Shotgun metagenomics on severe

and enduring AN at Karolinska

Institutet & University of Western

Australia

(54)

Genes

Microbiota

Deep Phenotyping

Binge Eating Genetics Initiative

(55)

BEGIN U.S.

Saliva-based DNA collection

5-site microbiota sampling

Deep longitudinal active &

passive phenotyping via RR and Apple Watch

N=5000

bulimia nervosa or binge-eating

disorder

(56)

BEGIN Sweden

Saliva-based DNA collection

Fecal microbiota sampling

16S & future shotgun metagenomics

Internet-based phenotyping National Register linkage

Eating Disorders Quality Register Linkage

N= ~4000

bulimia nervosa or binge-eating

disorder

(57)

To what end?

• These will be the largest studies of any phenotype to combine

– Genomics – Microbiota

– Deep phenotyping

• To rapidly and efficiently characterize the biology and behavior of these complex and debilitating disorders