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Supplementary information

Genome-wide association study identifies SESTD1 as a novel risk gene for lithium responsive bipolar disorder

Supplementary Methods

Swedish Quality Register for bipolar disorder (BipoläR) 2

Phenotype definition and assessment 2

Quality control for genotyping 5

Test of Hardy-Weinberg Equilibrium for imputed variant rs116323614 6

Heritability estimation for lithium-responsive bipolar disorder (BD) 6

Supplementary Tables and Figures

Table S1. Subject characteristics for patients with lithium assessment and genotype 8

Table S2. Corresponding number of sample of the objectively and subjectively defined

assessments for lithium response 9

GWAS comparing lithium responding with lithium non-responding BD patients

(Summary statistics in Table S3, quantile-quantile and Manhattan plots in Fig S1, associated

genetic regions in Table S4) 10

GWAS comparing lithium responding BD patients and healthy controls

(Summary statistics in Table S5, quantile-quantile and Manhattan plots in Fig S2, associated

genetic regions in Table S6, region plots of the most associated regions in meta-analysis in

Figure S3) 16

Table S7. Association results of top associated loci from meta-analyses for each sub-sample23

Table S8. Predicted genotype frequencies for rs116323614 in each sample and tests of Hardy-

Weinberg Equilibrium 24

Table S9. Association results for rs116323614 in male and female samples 25

Table S10. Univariate heritability estimates of lithium-responsive BD 26

References 27

1

Supplemental Methods

Swedish Quality Register for BD (BipoläR)

Swedish Quality Register for BD (BipoläR) contains individualized data on diagnoses (i.e.,

BD type 1, type 2, not otherwise specified, or schizoaffective disorder bipolar type), medical

intervention, and outcomes. It also captures basic clinical epidemiological data as well as

longitudinal data on the natural history and clinical course of the disease. Participation is

voluntary for the clinician as well as for the patients. The diagnoses were made according to

the DSM-IV-TR, but the use of structured interviews varies between participating units,

which include both private and public psychiatric outpatient health care units in Sweden.

Psychiatrists who register patients have often specialized in the treatment of mood disorders

and treatment of BDs in particular. Hence, BipoläR contains much more detailed phenotypic

information than other Swedish national registers and provides good validity and high data

quality. Patients were followed-up annually 2005–2013. Until June 2013 when the data were

extracted, 6429 BD patients were registered in BipoläR with the mean total follow-up time

3.1 years (SD=1.7, range 1-9 years).

Phenotype definition and assessment

Phenotype definition for Swedish sample

Subjective assessment included two branches. Participants from Stanley were interviewed

over the phone by trained nurses using a structured questionnaire. Provided a person had

taken lithium for at least 12 months at any point in life, he or she would be asked about the

therapeutic effect regardless of potential side effects. Responses were categorized into four

groups: 1) “Complete remission. No further episodes, became well” (N=660, 62.1%); 2)

2

“Clearly improved, but continued to suffer from mood episodes, or needed additional

treatment” (N=264, 24.9%); 3) “No or questionable treatment effect” (N=86, 8.1%); 4) “Do

not know or do not want to answer” (N=52, 4.9%).

Patients from S:t Göran were assessed by a psychiatrist using a standardized interview

protocol (the Affective Disorders Evaluation) which was previously used in the Systematic

Treatment Enhancement Program of Bipolar Disorder Program (STEP-BD).1 Response was

also categorized into four groups: 1) “Complete response” (N=77, 33.3%); 2) “Markedly

improved or somewhat improved, but continued to suffer from mood episodes, or needed

additional treatment” (N=20, 8.7%); 3) “No or doubtful treatment effect” (N=13, 5.6%). 4)

“No data or used lithium too short time” (N=121, 52.4%).

By adding an objective assessment lithium response in the Swedish sample, we aimed for a

phenotype definition that would correspond more closely to the UK-BDRN subgroup with

excellent and beneficial response to lithium (group 1 and 2 in the UK samples, see below).

We assessed the effectiveness of lithium in preventing mood episodes by using recurrence

data at yearly longitudinal follow-ups extracted from Swedish Quality Register from May

2004 until June 2013. Subjects who had used lithium for at least one year were included.

Responders were defined as having no mood episodes during follow-up (N=159, 16.9%),

while non-responders were those that had at least one mood episode during follow-up

(N=780, 83.1%). The extent to which subjective assessment and objective assessment were in

line with each other is shown in Supplementary Table S2.

Phenotype definition for UK sample

Lithium response information for participants from BDRN was collected by interviews and

reviews of clinical notes and was originally categorized into five groups:

3

1) “Objective evidence for excellent response to lithium prophylaxis” (i.e., frequency of

episodes reduced to <10% of frequency after lithium prophylaxis and/or 2 or more

episodes of illness occurring within weeks of cessation of lithium. This could only be

rated if at least 3 episodes of illness had occurred before lithium prophylaxis and

lithium response had been observed for at least 5 years.) (N=47, 3.0%);

2) “Objective evidence for beneficial response” (i.e., clear reduction in number and/or

severity of episodes following introduction of lithium prophylaxis. This could only be

rated if at least 3 episodes of illness had occurred before lithium prophylaxis and

lithium response had been observed for at least 3 years) (N=117, 7.4%);

3) “Subjective good response” (i.e., self-reported complete or partial remission, but with

an observation period too short to meet objective criteria (<=3 years)) (N=738,

46.8%);

4) “Unsure of response” (i.e., have been on lithium only for a couple of months, or had it

stopped after a brief period due to side effects) (N=603, 38.2%);

5) “No evidence of response to lithium” (i.e., no reduction in number and severity of

episodes following introduction of lithium prophylaxis) (N =73, 4.6%).

Harmonizing the datasets

We treat lithium response as a dichotomous trait based on the subjective and objective

measurements, respectively.

By using subjectively defined lithium response we maximize the sample size. In the Swedish

sample, a total of 1120 subjects had available assessments of lithium response together with

genotyping data that passed quality control. We compared patients who reported complete

remission on lithium (Group 1), N=737, 65.8%) with those who reported partial or no

response (Group 2) and 3), N=383, 34.2%). For the UK subjects, we defined the UK groups

4

1), 2) and 3) as subjective responders (N=902, 57.2%), and the UK groups 4) and 5) as

subjective non-responders to lithium (N=676, 42.8%). This method of categorization is

similar to dichotomous definitions proposed in several previous clinical and genetic papers.2-5

By using objectively defined lithium response, we arrive at a narrower phenotype definition

of lithium response. The definition of objective response in the Swedish sample is given

above. For the UK sample, we categorized the UK groups 1) and 2) as objective responders

(N=164, 10.4% of the total UK sample) and the UK group 5) as objective non-responders

(N=73, 4.6% of the total UK sample). Groups 3) and 4) lack long-term data. With longer

observation, cases in these groups might end up in the response or the non-response group.

We therefore chose to exclude groups 3) and 4) from the objective assessment of UK data.

Quality control for Genotyping

Swedish sample

The quality control exclusionary measures for Swedish subjects were: genotype missingness

rate >5%, ancestry outliers identified via multidimensional scaling (MDS), suspected sample

error or contamination (i.e., subject heterozygosity rate >10%), ambiguous genetic sex, and a

randomly selected member of any pair of subjects identified as related (pi-hat > 0.20).

Exclusionary measures for SNPs were: marked deviations from Hardy-Weinberg equilibrium

(P<1×10-6), SNP missingness rate >5%, minor allele frequency (MAF) <1%, differential

missingness based on affection status (P<1×10-6), and differential missingness based on

haplotype (P<1×10-10).

UK sample

5

The quality control exclusionary parameters for the BDRN sample were: subject

heterozygosity rate >15%, subject missingness rate >2%, ambiguous genetic sex, SNP

missingness rate >2%, MAF<1%, marked departure from Hardy-Weinberg equilibrium

(P<5×10-5), differential missingness for SNPs between cases and controls (P<1×10-3) and

differential missingness based on haplotype (P<1×10-10), population outliers identified via

multidimensional scaling, and a random member of each pair of related subjects (defined as

pi-hat >0.10).

Test of Hardy-Weinberg Equilibrium for imputed variant rs116323614

As the calculation for genotype frequencies is not straightforward in dosage (imputed) data, we

used the method provided in the paper “Approximate and Exact Tests of Hardy-Weinberg

Equilibrium Using Uncertain Genotypes”.6 Regarding potential skewing in genotype

distributions, we performed the exact tests of Hardy-Weinberg Equilibrium (HWE). The

results are shown in Table S8.

Heritability estimation for lithium-responsive BD

We first combined the two datasets (Sweden wave 2 and UK) and excluded variants only

existing in one sample or with ambiguous base pair position and strand. We then used GCTA

version 1.24 to filter for cryptic relatedness between individuals (cutoff value 0.025). A total

of 10 786 individuals and 382 330 SNPs were included in the final dataset.

To test for systematic discrepancy between the genotypes produced by the two microarrays

and validate the combined dataset, we did a benchmark analysis with GCTA to estimate the

heritability of BD. The result showed that the heritability of BD was 0.32 (95% CI 0.28 to

6

0.36) in this sample, which was similar to a previous estimate (0.25) in a study applying the

GCTA method.7

We then estimated the heritability of lithium-responsive BD phenotype with subjectively and

objectively defined lithium response, respectively. We specify the prevalence 0.30 since

previous literatures have reported that full lithium responders are about one-third among

lithium treated patients.8,9 We established statistical significance using the likelihood-ratio test

of specific hypothesis (H0: SNP-heritability = 0) and reported the asymptotic 95% CI

(calculated as 1.96 times the standard error).

7

Table S1. Subject characteristics for patients with lithium assessment and genotype

Sweden (N=1822)* UK BDRN (N=2577)Ever taken lithium (%) 61.5 61.2

Lithium responders

Lithium non-responders

Lithium responders

Lithium non-responders

Subjective measurement (available lithium assessment and genotype)

Sample size 737 383 902 676Sex (% male) 38.6 38.5 33.5 26.5Mean age at sampling(Standard deviation)

52.1±13.9 48.8±13.3 48.9±12.3 47.9±12.0

Bipolar disorder type I (%) 59.1 53.7 74.7 68.9Objective measurement (available lithium assessment and genotype)

Sample size 159 780 164 73Sex (% male) 39.6 37.8 43.2 28.8Mean age at sampling(Standard deviation)

57.7±11.9 49.6±13.7 52.2±11.9 48.6±12.4

Bipolar disorder type I (%) 57.9 50.3 80.5 83.6* Swedish sample consists of subjects participating in both the Stanley study and S.t Göran Project

8

Table S2. Corresponding number of sample of the two different assessments for lithium response

Subjective assessmentResponder Non-responder NA Total

Objective assessment

Responder 135 17 7 159Non-responder 324 319 137 780

NA 129 2 275 406Total 588 338 419 1345

The numbers in the table refer to subjects with available lithium assessment and genotype (passed genotyping quality control).

Abbreviations: NA, not applicable, could not be placed into either category.

9

Table S3. Summary statistics for GWAS comparing lithium responding with lithium non-responding bipolar disorder patients (Quantile-quantile and Manhattan plots shown in Fig S1)

Swedish sampleUK

BDRNMeta-

analysisAffymetrix 6.0 (wave 1)

OmniExpress arrays (wave 2)

Subjective measurement

Responders 149 588 902 1639Non-responders 45 338 676 1059

λGC 0.97 1.02 1.00 0.99Quantile-quantile plot A B C D

Manhattan plot I II III IV

Objective measurement

Responders - 159 164 323Non-responders - 780 73 853

λGC - 1.01 1.00 0.97Quantile-quantile plot - E F G

Manhattan plot V VI VII

* λGC: genomic inflation factor, calculated by the median observed χ2 statistic divided by expectation under the null*The quantile-quantile and Manhattan plots for all analyses are in Supplementary Figure S1

A B

10

C D

E F

G

12

I

II

III

13

IV

V

VI

14

VII

Fig S1: Quantile-quantile plot for association analyses of lithium responders vs non-responders; A: Sweden wave 1 subjective assessment, B: Sweden wave 2 subjective assessment, C: UK-BDRN subjective assessment, D: Meta-analysis for subjective assessment, E: Sweden wave 2 objective assessment, F: UK-BDRN objective assessment, G: Meta-analysis for objective assessment. Manhattan plot for association analyses of lithium responders vs non-responders; I: Sweden wave 1 subjective assessment, II: Sweden wave 2 subjective assessment, III: UK-BDRN subjective assessment, IV: Meta-analysis for subjective assessment, V: Sweden wave 2 objective assessment, VI: UK-BDRN objective assessment, VII: Meta-analysis for objective assessment.

15

Table S4. Summary of top loci for each analysis comparing lithium responders vs non-responders and genes located in these regions

Chr Index SNPA1/A2 Freq OR P-values N Position KB Genes

Sweden wave 1, subjective assessment

12 rs11060299 C/T 0.80 4.675.23×10-

6 68129841278-129886304

45ZNF84,ZNF26,TMEM13

2D,MIR1244-3

4 rs34521094 C/G 0.89 7.526.73×10-

6 10189959142-189992773

34 FRG2

3 rs4858400 A/G 0.85 4.678.86×10-

6243

22417440-22580784163

MIR4273,FRG2C

3 rs13085296 C/T 0.90 5.411.49×10-

5120

166748961-167275775

527

ZBBX,WDR49,SERPINI2


2 rs56177802 T/C 0.73 2.142.03×10-

9 61190955006-191038244

83 C2orf88

4 rs10013531 C/A 0.53 1.602.54×10-

6106

184452303-184499131

47 FRG2

17 rs3743991 T/C 0.64 1.632.60×10-

6 44 73588067-73717421129

SAP30BP,RECQL5,MYO15B,LOC643008,LOC100130933,LLGL2,ITGB

4

16 rs7185701 A/G 0.87 1.993.52×10-

6138

6652748-6785191132

RBFOX1

Sweden wave 2, objective assessment

6rs11422150

6G/A 0.88 0.43

1.13×10-

6170

31770265-32625494855

NOTCH4, MHC, many genes

19rs14118340

5G/A 0.78 0.50

1.44×10-

6 27 32747302-32979847233

ZNF507,KIR3DP1,KIR2DL4,DPY19L3

13rs11365348

6C/T 0.91 0.40

1.73×10-

6118

50224143-50771235547

TRIM13, ST13P4, MIR3613, many genes

1 rs56207132 C/T 0.85 0.912.64×10-

6 66 50602495-51512469910

OR4F16,OR4F29,LOC100133331,LOC100132287,FAF1,ELAVL4,DMR

TA2,CDKN2CUK-BDRN, subjective assessment

20 rs28691794 C/T 0.90 0.492.11×10-

6 65 61150190-61213367 63MIR133A2,MIR1-

1,C20orf200,C20orf166

2 rs10856800 C/G 0.47 1.432.32×10-

6 49 20716754-20752681 36 No genes

3rs15026564

1G/T 0.94 2.12

2.34×10-

6112

149155106-149252704

98 WWTR1,TM4SF4

19 rs8113341 A/G 0.20 0.662.60×10-

6 88 10125941-10193325 67RDH8,KIR3DP1,KIR2DL4,COL5A3,C3P1,C19o

rf66,ANGPTL6UK-BDRN, objective assessment

14 rs1956691 C/T 0.83 3.972.21×10-

6240

58171917-58448472277

No genes

13 rs11620153 A/G 0.47 0.352.89×10-

6175

66592665-66911823319

PCDH9

3 rs13095395 C/T 0.81 3.443.76×10-

6

129

56965656-57261340296

SPATA12,MIR4273,IL17RD,HESX1,FRG2C,ARH

GEF3,APPL1

3 rs1392230 G/T 0.81 3.445.60×10-

6117

118411464-118585110

174

No genes

16

We used LD clumping to aggregate association findings into genomic regions. Position=hg19 coordinates. Genes in these

regions or the 20-kb flanking regions were identified using gene tracks from the UCSC Genome Browser.

Abbreviations: Chr, chromosome; Index SNP, the single-nucleotide polymorphism with the strongest association in the

genomic region; A1/A2, reference and alternate alleles; Freq, frequency of reference alleles; OR, odds ratio; N, number of

SNPs in the reported region; MHC, major histocompatibility complex.

17

Table S5. Summary statistics for GWAS comparing lithium responders with controls (Quantile-quantile and Manhattan plots shown in Fig S2)

Swedish sampleCardiff sample

Meta-analysisAffymetrix 6.0

(wave 1)OmniExpress arrays

(wave 2)

Subjective measurement

Responders 149 588 902 1565Controls 2215 1271 5413 8899

λGC 1.01 1.04 1.04 1.05Quantile-quantile plot A B C D

Manhattan plot I II III IV

Objective measurement

Responders - 159 164 323Controls - 1271 5413 6684

λGC - 1.01 1.01 1.01Quantile-quantile plot - E F G

Manhattan plot V VI VII

* λGC: genomic inflation factor, calculated by the median observed χ2 statistic divided by expectation under the null*The quantile-quantile and Manhattan plots for all analyses are in Supplementary Figure S2

A B

18

C D

E F

G

19

I

II

III

20

IV

V

VI

21

VII

Fig S2: Quantile-quantile plot for association analyses of lithium responders vs controls; A: Sweden wave 1 subjective assessment, B: Sweden wave 2 subjective assessment, C: UK-BDRN subjective assessment, D: Meta-analysis for subjective assessment, E: Sweden wave 2 objective assessment, F: UK-BDRN objective assessment, G: Meta-analysis for objective assessment Manhattan plot for association analyses of lithium responders vs controls; I: Sweden wave 1 subjective assessment, II: Sweden wave 2 subjective assessment, III: UK-BDRN subjective assessment, IV: Meta-analysis for subjective assessment, V: Sweden wave 2 objective assessment, VI: UK-BDRN objective assessment, VII: Meta-analysis for objective assessment

22

Table S6. Summary of top loci for each analysis comparing lithium responders vs controls and genes located in these regions

Chr Index SNP A1/A2 Freq

OR P-value N Position KB Genes


9 rs10979017 C/G 0.99 0.20 1.08×10-8 4 110461462-110497099 36 No genes

12rs14649927

2C/T 0.98 0.17 2.71×10-7 38 84520335-85027937

508

ZNF84,ZNF26,MIR1244-3

2rs11592098

3C/A 0.99 0.15 4.73×10-7 4 207525730-207593030 67

MDH1B,LOC200726,DYTN

13 rs9542739 T/C 0.12 2.23 5.48×10-7 90 71993107-72366052373

DACH1


18 rs1442378 T/C 0.33 1.55 5.19×10-8 45 4050546-4071783 21 DLGAP1

7 rs6466030 T/C 0.62 0.68 4.04×10-7 388 104557060-105064593507

SRPK2,MLL5,LOC723809,LOC100216545,LHFPL3

15 rs4887200 G/C 0.95 0.41 7.57×10-7 13 88180809-88537816357

NTRK3

2 rs2091672 A/T 0.30 0.66 7.77×10-8 196 140567355-140782556215

No genes

Sweden wave 2, objective assessment

3 rs73186618 C/T 0.99 0.12 4.93×10-7 27 19791860-20004093212

RAB5A,MIR4273,FRG2C,EFHB,

C3orf48

11rs38641974

5-/AC 0.94 0.26 7.40×10-7 29 107643375-107797271

154

SLC35F2,RAB39

12rs18718043

8G/A 0.99 0.07 9.32×10-7 2 121791447-121909328

118

ZNF84,ZNF26,RNF34,MIR1244-

3,KDM2B,ANAPC511 rs71455013 T/A 0.84 0.42 1.26×10-6 30 22795964-22810983 15 GAS2

UK-BDRN, subjective assessment

16rs14158927

1A/C 0.96 2.93 1.36×10-6 1 81171896-81171896 0 PKD1L2

3 rs3936575 A/G 0.24 0.74 1.41×10-6 136 21644870-21783136138

ZNF385D,MIR4273,FRG2C

7rs20153782

2T/- 0.96 0.55 1.56×10-6 51 18095574-18479387

384

No genes

7rs19312109

9C/T 0.99 0.39 2.11×10-6 23 7477518-7819352

342

RPA3,MIOS,LOC729852,COL28A1

UK-BDRN, objective assessment

11rs14672760

1TA/- 0.99 0.22 1.22×10-7 19 112060319-112384063

324

TEX12,PTS,C11orf34,BCO2

3rs14215363

1C/A 0.99 0.20 1.35×10-7 222 38809692-39545741

736

XIRP1,WDR48,TTC21A, many genes

19 rs77866734 C/T 0.98 0.23 1.39×10-7 13 1528365-1642221114

UQCR11,TCF3,PLK5P,MEX3D,

MBD3,KIR3DP1,KIR2DL4,ADAMTSL5

10 rs28498397 T/C 0.98 0.24 2.21×10-7 228 124304753-124872079567

PSTK,LOC399815,IKZF5,FLJ46361,

many genesWe used LD clumping to aggregate association findings into genomic regions. Position=hg19 coordinates. Genes in these

regions or the 20-kb flanking regions were identified using gene tracks from the UCSC Genome Browser.

23

Abbreviations: Chr, chromosome; Index SNP, the single-nucleotide polymorphism with the strongest association in the

genomic region; A1/A2, reference and alternate alleles; Freq, frequency of reference alleles; OR, odds ratio; N, number of

SNPs in the reported region; MHC, major histocompatibility complex.

24

a

b

Figure S3. Region plots of the most associated region in meta-analysis results comparing lithium responders vs controls. SNPs are represented from genome build hg19/1000 Genomes Nov 2014 EUR. The purple diamond marks the most highly associated SNPs. (a) rs116323614 (p=2.74 x 10-8; OR=3.14). (b) rs146727601 (p=1.33 x 10-8; OR=3.98).

25

Table S7. Association results of top associated loci from meta-analyses for each sub-sample

Index SNP A1/A2 Sample Freq INFO OR 95% CI P-valueResponders vs non-responders, subjective assessmentsrs73918339 T/C Sweden wave 1 0.92 0.72 0.72 0.24-2.18 0.56

Sweden wave 2 0.91 0.93 0.66 0.46-0.96 0.03UK BDRN 0.90 0.76 0.49 0.37-0.66 2.11×10-6

rs7240206 C/G Sweden wave 1 0.11 0.83 1.48 0.61-3.56 0.39Sweden wave 2 0.09 0.91 0.56 0.40-0.78 6.70×10-4

UK BDRN 0.09 0.91 0.57 0.44-0.74 2.54×10-5

rs116927879 G/A Sweden wave 1 0.89 0.90 1.73 0.81-3.70 0.16Sweden wave 2 0.86 0.82 1.77 1.32-2.38 1.36×10-4

UK BDRN 0.84 0.86 1.41 1.14-1.74 0.001rs78295376 T/C Sweden wave 1 0.87 0.74 0.73 0.30-1.77 0.49


Responders vs non-responders, objective assessmentsrs438475 G/A Sweden wave 2 0.88 0.99 0.43 0.31-0.60 1.13×10-6

UK BDRN 0.87 0.96 0.73 0.39-1.37 0.33rs113262272 A/- Sweden wave 2 0.71 0.82 1.89 1.36-2.64 1.63×10-4

UK BDRN 0.71 0.73 2.01 1.21-3.35 0.007rs809 C/T Sweden wave 2 0.54 0.98 0.56 0.44-0.72 7.64×10-6

UK BDRN 0.48 0.99 0.73 0.49-1.09 0.13rs181812561 G/A Sweden wave 2 0.98 0.66 0.13 0.05-0.33 1.43×10-5

UK BDRN 0.98 0.64 0.06 0.00-4.29 0.20Responders vs controls, subjective assessmentsrs12144699 G/A Sweden wave 1 0.96 0.77 0.56 0.33-0.97 0.04


rs9834970 T/C Sweden wave 1 0.50 0.97 0.68 0.53-0.87 0.002Sweden wave 2 0.50 1.00 0.83 0.71-0.96 0.01UK BDRN 0.51 1.00 0.84 0.76-0.93 9.24×10-4

rs12493050 G/A Sweden wave 1 0.20 1.00 1.22 0.92-1.61 0.17Sweden wave 2 0.20 0.95 1.25 1.04-1.50 0.02UK BDRN 0.20 1.01 1.28 1.14-1.44 3.72×10-5

rs4947962 G/C Sweden wave 1 0.11 0.94 1.35 0.95-1.91 0.09Sweden wave 2 0.11 0.97 1.54 1.23-1.94 2.19×10-4

UK BDRN 0.11 0.94 1.27 1.08-1.48 0.003Responders vs controls, objective assessmentsrs146727601 -/TA Sweden wave 2 0.01 0.74 2.84 1.15-7.14 0.02

UK 0.02 0.82 4.53 2.56-7.69 1.22×10-7

rs116323614 A/G Sweden wave 2 0.02 0.86 2.84 1.41-5.88 0.004UK 0.03 0.79 3.30 2.00-5.26 1.97×10-6

rs77866734 C/T Sweden wave 2 0.99 0.90 0.51 0.18-1.43 0.20UK 0.98 0.64 0.23 0.13-0.39 1.39×10-7

rs142643109 T/G Sweden wave 2 0.99 0.74 0.25 0.09-0.68 0.006UK 0.98 0.75 0.29 0.16-0.51 1.85×10-5

Abbreviations: Index SNP, the single-nucleotide polymorphism with the strongest association in each meta-analysis; A1/A2,

reference and alternate alleles; Freq, frequency of reference alleles; INFO, imputation info score; OR, odds ratio; CI,

confidence interval.

26

Table S8. Predicted genotype frequencies for rs116323614 in each sample and tests of Hardy-

Weinberg Equilibrium

Sample NNumber of subjects by imputed

genotype Exact Tests of Hardy-Weinberg EquilibriumAA(%) AG(%) GG(%)

Sweden wave 1 3141 2 (0.0007) 132 (0.04) 3007 (0.96) P=0.45

Sweden wave 2 3755 2 (0.0006) 167 (0.04) 3586 (0.95) P=0.84

UK 8035 6 (0.0007) 441 (0.05) 7588 (0.94) P=0.40Method for calculation was from “Approximate and Exact Tests of Hardy-Weinberg Equilibrium Using Uncertain

Genotypes”.6

27

Table S9. Association results for rs116323614 in male and female samples

Sample SexNo of

responder vs. control

Ref allele Freq

OR SE 95% CI P-value

Test for difference between

ORs

Sweden wave 2

Male 63:632 0.02 2.16 0.58 0.69-6.73 0.19

P=0.51Female 96:639 0.02 3.53 0.48 1.38-

9.04 0.008

UKMale 71:2805 0.03 3.00 0.42 1.32-

6.83 0.009P=0.80Femal

e 93:2608 0.03 3.43 0.31 1.87-6.30 8.63×10-5

Meta-analysi

s

Male 134:3437 0.03 2.67 0.34 1.37-5.22 0.004

P=0.55Female 189:3247 0.03 3.46 0.26 2.07-

5.78 2. 19×10-6

All* 323:6684 0.03 3.10 0.21 2.07-4.64 3.93×10-8

* Association analysis with adjustment for sex.

Abbreviations: Ref allele Freq, frequency of reference alleles; OR, odds ratio; SE, standard error; 95% CI, 95% confidence

interval.

28

Table S10. Univariate heritability estimates of lithium-responsive BD

Phenotype Cases/Controls* Heritability (h2)* 95%CI P-value*

BD 3824 / 6247 32% 28 to 36 <0.01

Lithium-responsive BD

Subjective definition

Objective definition

1430 / 6247 29% 23 to 36 <0.01

307 / 6247 25% 0 to 51 0.03

* Numbers of cases and controls are after excluding one of each pair of individual with cryptic relatedness using GCTA; h2 is

SNP-heritability on the liability scale; P-values are from likelihood tests of null hypothesis of heritability being 0.

Abbreviations: BD, bipolar disorder; CI, confidence interval

29

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