1

WHOLE EXOME SEQUENCING

ANALYSIS OF KOREAN PATIENTS

WITH EARLY ONSET

NEURODEGENERATIVE DISEASE

Eva Bagyinszky

Gachon University

Department of BioNano Technology

2018. 11. 09.

Disclosure

There are no conflicts of interest and nothing to disclose

3

Alzheimer’s disease

Alzheimer’s disease: 2 types of AD: EOAD & LOAD

EOAD (familial): 3 genes in EOAD: APP, PSEN1 and PSEN2

Not all EOAD patients had mutations

20 years 30 years 40 years 50 years 60 years

PSEN1

PSEN2

APP

APOE + other genes

Age

EOAD LOAD

65 years

Down syndrome

Bird et al. 1999

4

AD Mutation frequencies

• Familial AD: 5-10% of all AD cases

• Issue: in the most patients, the disease causing factors

remained unexplained

• Goal: finding out the missing etiology of EOAD

Genes penetrance Reported mutations

APP 1-1.5% of all familial AD

52

PSEN1 3-7% of all familial AD 242

PSEN2 less than 1% 47

Our data in APP, PSEN1 and PSEN2 mutation codon Remarks References

APP Gly708Gly GGC->GGT(2) Silent mutation, not pathogenic Balbín et al. 1992

Val669Leu GTG->CTG (3) Novel mutation, may be involved in AD In preparation

Val604Met GTG->ATG (1) Located outside of amyloid peptide region Accepted to NDT (2018)

Pro484Ser CCA->CTA (1) Located outside of amyloid peptide region

Located outside of amyloid

peptide region

Thr297Met ACG->ATG (1)

Val225Ala GTA->GCA (1)

PSEN1

Val96Phe GTC->TTC (2) Pathogenic mutation, described in Japan before.Found in 2 Malaysian

siblings

In preparation

Thr116Ile AAC->ATC (3) Novel in Korea, described in Europe before

Pathogenic mutation, associated with EOAD

Raux et al. 2005 La Bella et al.

2004, Published in 2018 (IJMS)

Thr119Ile ACA->ATA (1) Novel mutation. May be involved in AD In preparation

His163Pro CAT->CCT (1) Novel mutation. Involved in EOAD Published in 2012 (NSL)

Trp165Cys TGG->TGC (1) Pathogenic mutation, described in Europe before Campion et al. 2005, in

preparation

Glu184Gys GAA->GGA(1) Found in a Thai patient

Known mutation, described in Europe before

Wallon et al. 2010

In preparation

Gly209Ala GGA->GCA (2) Novel mutation, might be involved in EOAD

Detected in a Korean AD patient

Published in 2016

(BMC Neurology)

Leu226Phe CTC->TTC (1) Known, pathogenic mutation. Novel in Korea.

Involved in EOAD or FTD.

Published in 2016, (Clinical

Interventions in Aging)

Leu232Pro CTC->CCC (1) Novel mutation, might be involved in EOAD

Detected in a Korean AD patient

Published in 2017

(Neurobiology of Aging)

Glu280Lys GAA->AAA (3) Found in 2 Malaysian siblings

Probable pathogenic mutation

Published in 2015 (NDT)

Ala285Val GCT->GTT (1) Known mutation, found in Japan before

Found in a Korean EOAD patient

Ikeda et al. 1996

In preparation

Gly417Ala GGT->GCT (1) Novel mutation, found in a Korean AD patient. May be involved in

AD

Published in 2018

(Neurobiology of Aging)

PSEN2

Arg62Cys CGC- >TGC (1) Known mutation. Novel in Korea. Might be involved in LOAD. Sleegers et al. 2004, Published

in 2017 (Clinical Interventions in

Aging)

Asn169His CAT->AAT (1) Known mutation, pathogenic nature unclear

Discovered in China before

Accepted recently

(Clinical Interventions in Aging)

Val214Leu GTG->TTG (3) Novel, first missense PSEN2 mutation in Asia.

Might be involved in AD or dementia. Published in 2014.

Published in 2014

(BMC Neurology)

6

AD-associated pathways

Amyloid pathway is not

the only way for AD

progression.

GWAS and WGS studies

provided the discovery of

novel genes

Additional mechanisms:

Impairment in Tau,

inflammation, metabolism-

associated pathways may

be important

Several possible risk

genes were identified for

AD

http://www.cell.com/trends/genetics/fulltext/S0168-9525(09)00252-2

7

Problems with disease diagnosis

Pievani, et al. 2014

8

Problems with disease diagnosis

Moussaud et al. 2014.

Clinical and pathological overlap

9

Current approach: Whole exome sequencing

Diagnosis of patients with early

onset dementia

(NINCDS-ADRDA)

APOE

genotyping Sample

preparation

WHOLE EXOME SEQUENCING

Analyzing the known disease-causing and

risk factor genes (100)

Verification (standard sequencing)

Functional

studies In silico

predictions

DISEASE ASSOCIATED MUTATION

Disease No Additional genes to our gene panel

AD

40 PSEN2, S100A9, CR1, BIN1, TREM2, CLU, CTNNA3,

DNMBP, SORL1, PICALM, BACE1, LPR6, PSEN1, ADAM10,

ABCA7, CD33, TOMM40, APP, MS4A4A, MS4A6E, TM2D3,

CD2AP, EPHA1, CASS4, PLD3, HLA-DRB5, HLA-DRB1,

INPP5D, DSG2, CDH12, CDH18, MEF2C, NME8, PTK2B,

SLC24A4, RIN3, ZCWPW1, ACE, MTHFD1L

PD

22 PINK1, PARK7, PARK9, GBA, SNCA, PARK2, LRRK2;

ACMSD, CD157/BST1, FBXO7, FGF20, GAK, GIGYF2,

GPNMB, HIP1R, LAMP3, PLA2G6, STBD1, STK39, STX1B,

SYT11, VPS35

ALS &

FTD

30 TDP43, CHMP2B, SIGMAR1, VCP, FUS, GRN, MAPT,

UBQLN2, ALS2, TAF15, FIG4, OPTN, DAO, HNRNPA1,

SOD1, ANG, VAPB, SQSTM1; ATXN1, ATXN2, EWSR1,

HNRNPA2B1, PFN1, SETX, TMEM106B, CCNF, PPT1, TBK1,

DCTN1, NEK1

Other

disease

8 SPAST, CYP7B1, SPG11, CSF1R, NOTCH3, PRNP; CTSA;

HTRA1

10

Workflow of WES data

Workflow of WES analysis WES data on a missense mutation

WES data on an indel

Current approach: Whole exome sequencing

11

Strategy of mutation analysis of WES data WES data: 3-4 million mutations

Common

mutations

Rare mutations

Coding noncoding

Splice site Non-splice

site Synonymous Missense,

nonsense

frameshift Codon bias?

Missing or rare in unaffected

population (ExAC, 1000Genomes)

In silico predictions

Segregation analysis (family

members)

Transcriptome analysis

Cell studies

Transcriptome

analysis

Disease

associated

databases

Possible risk

Probable pathogenic variant

12

Dilemmas

• Several EOAD patients are negative for APP, PSEN1 and

PSEN2 mutations

• WES data reveals several mutations, and it is unknown,

which could be important

• “Common disease variant”?

• Pathway analysis:

• ClueGo and STRING tools

13

“Common disease common variant” -CD-CV

• Some rare variants in coding/regulatory genes lead to

susceptibility to complex polygenic diseases

• Plan is screening for mutations, appearing in affected

individuals, but missing in the unaffected ones, and also in

the population databases (ExAC, 1000Genomes)

• These mutations are “common mutations in AD”, which

appear only in AD

• Linkage study: mutation appear in affected family members,

but missing in the unaffected ones

14

Possible AD risk genes

15

ABCA7 mutations

Rare mutations:

• M354T (B)

• W435R (D)

• D964E (D)

• T967M (D)

• A1196T(D)

• W1214X

• R1496C (D)

• R1505H (B)

• S1509I (D)

• G1573D (D)

• V1562I (B)

• I1690T (D)

• V1729M (B)

• R1780Q (D)

• G1741V (D)

• D1791V (D)

• G1870V (D)

• C1988F (D)

• R1921P (D)

• F2071C (D)

Sakae et al. J. Neursci. 2016

16

SORL1 mutations

17

CR1 mutations

Rare mutations

• T132P (B)

• T173A (B)

• T1358M (B)

• N1990S (B)

• G2171V (D)

• V2218A (B)

T173A

N1990S

G2171V

V2218A

T132P

T1358M

Zhu et al. Molecular Neurobiology 2015

18

TREM2 mutations

TREM2 mutations

• V166M (D)

• E177K (B)

• S183C (D)

• L211P (B)

E177K

L211P

E177K

L211P

S183C

V166M

S183C

V166M

Kober and Brett, Journal of Molecular Biology 2017

Hickman and El Khoury, Biochem Pharmacol. 2014

19

ADAM10 mutations

ADAM10 mutations

• G168D (D)

• I563L (B)

• T255A (B)

• D481G (D)

T255A

D481G

I563L

Mutations may

impair a-

secretase

activity?

G168D

Saftig and Lichtenthaler, Prog Neurobiol. 2015

20

Non-AD associated genes

• GRN: FTD-associated gene, involved in cell survival (3)

• MAPT: FTD-associated gene, may affect AD through Tau

impairment (8)

• NOTCH3: CADASIL-associated gene, may be involved in

AD through NOTCH signaling (10)

• CSF1R: leukoencephalopathy gene, some patients with

CSF1R mutations were diagnosed with AD (6)

• PRNP: Prion disease gene, some mutations were observed

in AD patients (4)

• PD-associated genes: Some AD patients presented

Parkinsonism: LRRK2 (10); PARK2 (5); PINK1 (3)

PRNP and Alzheimer’s disease

• Two prion mutations: M232R and V180I were frequently found among AD and dementia (non-CJD) patients

• They could be involved in CJD, but low penetrance

• Possibly involvement in non-CJD associated dementia

• Alzheimer’s disease and prion disease could have pathological overlap: CJD patients may be diagnosed with AD

Example of 3D modeling: V180I mutation, which could disturb the hydrophobic core of prion

GRN mutations among dementia patients

• GRN R298H: found in a patient with mixed dementia, possibly involved in CBS/FTD, AOO could be in the 60s

• R564C is possible risk for Alzheimer’s disease. Possibly associated with reduced GRN levels

• R110X: Found in a family from Philippines, diagnosed with FTD. Novel in Asia

GRN R110X 3D model

MAPT mutations among dementia patients

• MAPT is a causative gene of FTD and possible risk factor for AD

• Several mutations were found in MAPT, which may not be pathogenic, or possible risk factor for dementia

• P140S, D177W, K204R, G208D, Q230R and P513T were found among AD/dementia patients

• May be risk factor for AD/dementia?

• One ataxia patient had multiple non-pathogenic MAPT mutations: P202L, D285N, V289A, R370W and S447P

• It is unclear, how these several mutations could affect on disease

24

Pathway analysis for one patient

• Example: 28 years male patient

• He was suspected of having prion disease, and may

diagnosed with ataxia. Symptoms are progressive dementia,

movement discoordination, weakness and myoclonic jerk.

• Virtual gene panel analysis was performed

• No pathogenic PRNP mutation was found (M129V-but it may

not be responsible for disease)

• MAPT: multiple rare, possible risk mutations (P202L; D285N;

V289A; R370W; S447P)

• Additional risk mutations in SORL1, ABCA7, LRRK2 genes

25

ClueGo pathway analysis for an

ataxia/dementia patient

26

STRING pathway analysis for an ataxia/

dementia patient

27

ClueGo pathway analysis for an AD patient

28

ClueGo pathway analysis for an FTD patient

29

Summary

• Several common and rare variants have been identified by

WES in the known disease causative and risk genes

• A more extensive analysis of 100genes could be relatively

effective approach in mutation screening and possible disease

risk analysis

• The LOAD risk genes, such as ABCA7, SORL1 or CR1 could

impact on the onset of EOAD

• Some non-AD genes, such as PRNP, GRN and MAPT may play

a role in AD

30

Summary

• In this study, whole exome analysis was performed on

AD/dementia patients

• Rare variants in the known risk genes were in focus

• In silico studies and screening in databases were already

performed on mutation to predict their involvement in disease

• Pathway analyses could also be helpful on the prediction of

pathways

• However, these methods may not be enough

• Transcriptome or in vitro studies are needed

31

Summary WES data: 3-4 million mutations

Common

mutations

Rare mutations

Coding noncoding

Splice site Non-splice

site Synonymous Missense,

nonsense

frameshift Codon bias?

Missing or rare in unaffected

population (ExAC, 1000Genomes)

In silico predictions

Segregation analysis (family

members)

Transcriptome analysis

Cell studies

Transcriptome

analysis

Disease

associated

databases

Possible risk

Probable pathogenic variant

May be useful

strategy in genetic

screening and

WES analysis

32

Future directions

• Cell studies on the variants to find our their possible role in

neurodegeneration

• Transcriptomic analysis

• More deep analysis of WES data by BioPython or R-

software to find possible novel candidate genes for AD and

dementia risk

• Comparison of mutations in AD and CJD sets

• Screening the family members of AD patients and compare

their data

33

Thank you for the attention