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Lynn	Petukhova,	Ph.D.	
lynn.petukhova@columbia.edu	
Assistant	Professor	
Columbia	University	
	
Alopecia	Areata	Research	Summit	
December	5,	2018	
Vagelos College of
Physicians and Surgeons
the	set	of	genetic	variants	that	contribute	to	a	disease	in	the	population	
Human	genetics	studies	
genetic	architecture	
polygenic	risk	monogenic	causes	
genetic	architecture	of	chronic	disease	
§  pathway overview, cell type
§  population relevance of target
§  genetic risk scores
§  interpretable biology
§  drug target identification
§  familial risk
genome-wide	association	studies	(GWAS)	linkage,	exome	sequencing	
(SNPs)	(mutations)
Genetic	architecture	of	Chronic	Diseases	
Breast	Cancer	 BRCA1,	BRCA2	 TP53,	CHEK2,	PALB2,	ATM,	CDH1,	RECQL,	FANCM	 122,977	cases	 +200		
[BRCA1]	
IBD	 NOD2	 ADAM17,	AICDA,	BTK,	CYBA,	CYBB,	DCLRE1C,	DOCK8,	G6PC3,	GUCY2C,	
HPS1,	HPS4,	HPS6,	ICOS,	IKBKG,	IL10,	IL10RA,	IL10RB,	IL21,	IPEX,	ITGB2,	
LRBA,	MEFV,	MVK,	NCF1,	NCF2,	NCF4,	PIK3R1,	PLCG2,	SLC37A4,	STXBP2,	
TTC37,	TTC7A,	WAS,	XIAP,	PRDM1,	NDP52	
25,000	cases	 +200		
[NOD2]	
Atopic	Dermatitis	 FLG	 ADA,	ADGRE2,	ARPC1B,	CARD11,	CARMIL2,	CDSN,	CHD7,	DCLRE1C,	DOCK8,	
DSG1,	DSP,	ERBB2IP,	FOXP3,	IFNGR1,	IL2RA,	IL2RG,	IL4RA,	IL7RA,	JAK1,	KIT,	
LIG4,	MALT1,	PGM3,	PLCG2,	RAG1,	RAG2,	SPINK5,	STAT1,	STAT3,	STAT5,	
STAT5B,	TGFBR1,	TGFBR2,	TPSAB1,	WAS,	WIPF1,	ZAP70	
18,900	cases	 31	
[FLG]	
Alzheimer’s	 APP,	PSEN1,	
PSEN2	
APOE,	AKAP9,	CD33,	CR1,	EPHA1,	INPP5D,	NME8,	SORL1,	TREM2,	THBS2,	
PLEKHG5	
42,000	cases	 21	
[PSEN1]	
LDL	 PCSK9,	LDLR	 APOB,	LDLRAP1,	ABCG5,	ABCG8	 8,000	total	 38		
[	LDLR,	PCSK9]	
Disease	 Linkage	 Additional	monogenic	genes	 Cohort	 Loci	
Monogenic	(mutations)	
linkage	analysis,	exome	sequencing	
Polygenic	(SNPs)	
GWAS	
AA	 3,000	cases	 14	
Type	2	diabetes	 HNF4A,	GCK	 INS,	BLK,	ABCC8,	KCNJ11,	HNF1A,	PDX1,	HNF1B,	NEUROD1,	KLF11,	CEL,	
PAX4,	APPL1	
47,979	cases	 76	
[HNF4A,	GCK]
Genetic	architecture	of	Chronic	Diseases	
Breast	Cancer	 BRCA1,	BRCA2	 TP53,	CHEK2,	PALB2,	ATM,	CDH1,	RECQL,	FANCM	 122,977	cases	 +200		
[BRCA1]	
IBD	 NOD2	 ADAM17,	AICDA,	BTK,	CYBA,	CYBB,	DCLRE1C,	DOCK8,	G6PC3,	GUCY2C,	
HPS1,	HPS4,	HPS6,	ICOS,	IKBKG,	IL10,	IL10RA,	IL10RB,	IL21,	IPEX,	ITGB2,	
LRBA,	MEFV,	MVK,	NCF1,	NCF2,	NCF4,	PIK3R1,	PLCG2,	SLC37A4,	STXBP2,	
TTC37,	TTC7A,	WAS,	XIAP,	PRDM1,	NDP52	
25,000	cases	 +200		
[NOD2]	
Atopic	Dermatitis	 FLG	 ADA,	ADGRE2,	ARPC1B,	CARD11,	CARMIL2,	CDSN,	CHD7,	DCLRE1C,	DOCK8,	
DSG1,	DSP,	ERBB2IP,	FOXP3,	IFNGR1,	IL2RA,	IL2RG,	IL4RA,	IL7RA,	JAK1,	KIT,	
LIG4,	MALT1,	PGM3,	PLCG2,	RAG1,	RAG2,	SPINK5,	STAT1,	STAT3,	STAT5,	
STAT5B,	TGFBR1,	TGFBR2,	TPSAB1,	WAS,	WIPF1,	ZAP70	
18,900	cases	 31	
[FLG]	
Alzheimer’s	 APP,	PSEN1,	
PSEN2	
APOE,	AKAP9,	CD33,	CR1,	EPHA1,	INPP5D,	NME8,	SORL1,	TREM2,	THBS2,	
PLEKHG5	
42,000	cases	 21	
[PSEN1]	
LDL	 PCSK9,	LDLR	 APOB,	LDLRAP1,	ABCG5,	ABCG8	 8,000	total	 38		
[	LDLR,	PCSK9]	
Disease	 Linkage	 Additional	monogenic	genes	 Cohort	 Loci	
Monogenic	(mutations)	
linkage	analysis,	exome	sequencing	
Polygenic	(SNPs)	
GWAS	
AA	 3,000	cases	 14	
Type	2	diabetes	 HNF4A,	GCK	 INS,	BLK,	ABCC8,	KCNJ11,	HNF1A,	PDX1,	HNF1B,	NEUROD1,	KLF11,	CEL,	
PAX4,	APPL1	
47,979	cases	 76	
[HNF4A,	GCK]	
BRCA1	mutations	among	breast	cancer	patients
Preliminary	Evidence	for	Alopecia	Areata	Mutations	
Limitations	
§  Small	sample	size	(n=28	families)	
§  Sparse	markers	(n=300)
Linkage	Analysis	Rationale	
50,000	variants	in	a	human	exome	
1,000	mutations	affect	protein	structure	
	
Parent-child	transmission	reduces	the	number	of	candidate	mutations	by	half.	
Disease	co-segregation	can	further	eliminate	substantial	genomic	regions.		
Exomes are noisy.
What	 How	
Linkage	Analysis	Method	
B	 C	D	A	
mutation
Linkage	Analysis	Analytic	Plan	
1.	Use	tagSNPs	to	identify	cosegregating	haplotypes	
2.	Finemap	regions	by	testing	cosegregating	
tagSNPs	for	association		
3.	Map	associated	tagSNPs	to	all	genic	SNPs	to	
identify	candidate	genes.	
4.	Use	exome	sequencing	data	to	screen	candidate	
genes	for	mutations	that	alter	protein	sequence.
Cohorts	constructed	from	the	National	Alopecia	Areata	Registry	
Discovery	Cohort	
genotype	38	families,	exome	sequence	for	28	probands	
Replication	Cohort	
§  Exome	sequence	for	108	patients	who	
report	family	history.	
§  Exome	sequence	for	620	patients	who	
report	no	family	history
Identify	Cosegregating	Haplotypes	
chr cytoband snp start start Hg19 snp stop stop Hg19 region size gene count max NPL LOD
1 1p36.1 rs10794531 26,694,245 rs9438620 26,716,136 21,891 1 1.08
1 1p13.2 rs155646 112,688,022 rs3128373 112,858,294 170,272 0 1.04
1 1q23.3 rs4657210 162,587,423 rs1704745 162,693,795 106,372 1 1.06
2 2q12.1 rs7571700 105,189,937 rs2679852 105,797,790 607,853 2 1.13
2 2q36.1-q37.3 rs2098533 225,182,419 rs12469535 243,044,147 17,861,728 158 4.17
4 4q34.3 rs1991983 182,454,723 rs6821430 182,499,174 44,451 0 1.31
5 5q13.1-q13.3 rs2047588 71,578,902 rs2114950 76,726,202 5,147,300 36 1.15
5 5q21.2 rs11955569 103,472,789 rs2034227 103,647,014 174,225 0 1.01
5 5q33.1-q34 rs4958486 151,058,334 rs10515827 160,754,957 9,696,623 49 1.71
6 6p12.2-q15 rs4715280 51,974,289 rs1504292 91,637,689 39,663,400 133 2.31
6 6q22.31-q24.1 rs9385268 123,041,722 rs7744152 139,663,885 16,622,163 84 2.18
8 8p23.1 rs7843504 8,439,068 rs7463440 12,652,105 4,213,037 37 1.9
9 9p24.3 rs10964134 204,201 rs755383 863,635 659,434 4 1.65
12 12q21.33-q23.1 rs2897852 90,768,440 rs11612901 96,221,318 5,452,878 30 1.71
15 15q22.2 rs11630244 60,021,637 rs7174483 60,123,836 102,199 0 1.02
17 17q25.3 rs1869932 77,318,565 rs2241886 78,113,832 795,267 9 1.13
18 18p11.21 rs1149360 13,540,713 rs3760534 13,874,975 334,262 4 1.09
18 18q21.2-q21.31 rs1105471 45,086,502 rs554192 55,784,763 10,698,261 42 1.27
20 20q13.11-q13.12 rs6065582 41,771,701 rs2179069 43,507,254 1,735,553 23 1.52
22 22q13.2 rs2072884 43,436,169 rs695537 43,769,871 333,702 6 1.05
Identified	in	Martinez-Mir	et	al.
Results:	Variant	Filtering	
10,000,000
373
6,688
SNPs Genes
11,272
300,000
Mutations
In the genome.
Genotyped TagSNPs
with evidence for linkage
and family-based association.
SNPs tagged by 373 SNPs.
Exome mutations (f<.05) in proband that alters protein sequence
and in a region with evidence for cosegregation with AA in proband’s family
~18,000
619
179
Genotype 38 families in discovery cohort
Exome sequence 28 probands in discovery cohort
223
148
108
87
Same mutation (f<.05) seen in replication cohort
Exome sequence replication cohort of 108 probands
New mutation (f<.001) in a same gene in replication cohort
5843
Exome sequence in a cohort of nonfamilial 620 patients
10349
16168union
49664New mutation (f<.001) in a same gene in replication cohort
701
Results:	Functional	connections	among	64	genes	
Term Count Fold Enrichment PValue
GO:0030574-collagen catabolic process 5 21.86 7.5E-05
GO:0005578-proteinaceous extracellular matrix 7 7.80 2.5E-04
GO:0030198-extracellular matrix organization 6 8.57 6.2E-04
GO:0005201-extracellular matrix structural constituent 4 17.08 0.002
GO:0050790-regulation of catalytic activity 4 16.96 0.002
GO:0030334-regulation of cell migration 4 15.13 0.002
GO:0005604-basement membrane 4 15.13 0.002
GO:0005581-collagen trimer 4 12.99 0.003
GO:0005788-endoplasmic reticulum lumen 5 7.78 0.004
GO:0007155-cell adhesion 7 4.27 0.005
GO:0043231-intracellular membrane-bounded organelle 7 3.75 0.010
Conclusion	and	Future	Directions	
§  We	have	prioritized	64	candidate	genes	and	701	variants	as	potential	monogenic	causes	
of	alopecia	areata.	
§  This	gene	set	enriches	pathways	and	gene	ontology	terms	that	suggests	the	ECM	as	a	
potential	mediator	of	alopecia	areata	pathogenesis	and	provides	a	rationale	for	future	
studies	of	ECM	integrity	and	signal	transduction	in	patient	samples.	
§  We	will	be	performing	genic	burden	testing	and	variant	association	testing	using	exome	
data	in	a	cohort	of	10,000	controls.		We	also	will	validate	the	cosegregation	of	a	select	set	
of	variants	by	genotyping	family	members.
Acknowledgements	
National Alopecia Areata Registry
Angela Christiano
Vera Price
Maria Hordinsky
David Norris
Madeline Duvic
NIAMS 1P30 AR069632-01
NIAMS 1P50 AR070588-01
Christiano Lab
Stephanie Erjavec
Alexa Abdelaziz
Tarek Yammany
Angela M. Christiano
AACORT core services
Sahar Gelfman
Aris Floratos
The Feinstein Institute for Medical Research
Annette Lee
Peter Gregersen
Baylor College of Medicine
Wei V. Chen
Christopher Amos

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