Genetic basis of rheumatological disease.pptx

1. Genetic basis of
Rheumatological diseases
Dr. Ali Alsarhan, MBCHB
Senior Paediatrics Resident Doctor- PGY4
SCFHS (Saudi Board) Trainee
Al-Jalila Children’s Specialty hospital / Dubai-UAE

2. Disclosure
• I have no actual or potential conflict of interest in relation to
this presentation.

3. Objective
• Understand the genetic tests use in Rheumatological
diseases
• Identify the importance of theses genetic tests.
• Real life scenarios of which genomic tests have changed
the clinical approach.

4. Introduction
• Rheumatological diseases in children are various. They Chronically
impact multi-organs and cause damage which sometimes can be
irreversible.
• Why ? Most of the times we don’t understand the reason.
• Pediatrics rheumatology continues to be an evolving branch, that we
are still exploring.
• Laboratories and imaging modalities are not always definitive.

5. • Revolution in medicine allowed better understating of the mechanism
of diseases including several proinflammatory pathways and their
role in autoinflammatory disorders including the very famous ancient
disease Familial Mediterranean Fever.
• Targeted drugs are very popular now in treating these disorders,
including IL1 blockers and TNF blockers.
• Many Rheumatological diseases have been associated with primary
immunodeficiency.

6. The addressed
impact

7. • In our study, we present the role of genetic testing in establishing the
diagnosis, explain unusual features, or elucidate causes of limited
response.
• In the cohort, we had 71 patients , and genetic testing was
performed for the following :
1. workup of suspected autoinflammatory disorders and periodic fever
syndromes
2. difficult‐to‐treat inflammatory eye disease
3. difficult‐to‐treat autoimmune connective tissue diseases
4. suspected primary noninflammatory connective tissue diseases
presenting with musculoskeletal manifestations

10. Modalities

11. Quick technical points
• Genomic DNA was extracted from peripheral blood cells using
standard DNA extraction protocols (Qiagen)
• Fragmentation by ultrasonication (Covaris)
• Short fragments (300–400 bp) were generated using the
SureSelectXT Kit (Agilent).
• The enriched libraries underwent NGS (2 × 150 bp) using the SP
flow cell and the NovaSeq platform (Illumina).

12. Quick technical points
• Disease databases, such as ClinVar and the Human Gene Mutation
Database (HGMD), were used.
• Only rare variants were retained for downstream filtration and
analysis.
• For targeted gene analysis, rare, known pathogenic or novel,
variants in the relevant genes associated with the patient's indication
were retained for interpretation

13. List of gene panels used
• AJCH autoinflammatory (AID) 37‐gene panel (N= 11 patients)
• ACP5, ADA2, ADAM17, ADAR, AP1S3, CARD14, COPA, ELANE, IFIH1, IL1RN, IL36RN, LPIN2, MEFV, MVK, NLRC4, NLRP1, NLRP12, NLRP3, NOD2, OTULIN, PLCG2, POLA1, PSMB8, PSTPIP1, RNASEH2A, RNASEH2B, RNASEH2C,
SAMH D1, SH3BP2, SLC29A3, STING1, TADA2A, TNFAIP3, TNFRSF1A, TREX1, TRNT1, USP18.
• CGC autoinflammatory 34‐gene panel (N = 4 patients)
• ACP5,& ADAM17, ADAR, AP1S3, CARD14, CECR1, COPA, IFIH1, IL1RN, IL36RN, LPIN2, MEFV, MVK, NLRC4, NLRP1, NLRP12, NLRP3, NOD2, OTULIN, PLCG2, POLA1, PSMB8, PSTPIP1, RNASEH2A, RNASEH2B, RNASEH2C, SAMHD1,
SH3BP2, SLC29A3, TMEM173, TNFAIP3, TNFRSF1A, TREX1, USP18.
• Moyamoya disease (N = 1 patient)
• RNF213.
• Periodic fever syndrome 31‐gene panel (N = 5 patients)
• AP1S3, CARD14, CECR1, ELANE, FOXD3, HAX1, IL10, IL10RA, IL10RB, IL1RN, IL36RN, LPIN2, MEFV, MVK, NLRC4, NLRP1, NLRP12, NLRP3, NLRP7, NOD2, PLCG2, PSMB8, PSTPIP1, RAB27A, RBCK1, RNF31, SH3BP2, SLC29A3,
TMEM173, TNFRSF11A, TNFRSF1A.
• Complement deficiencies 33‐gene panel (N = 1 patient)
• C1QA, C1QB, C1QC, C1R, C1S, C2, C3,C4A, C4B, C5, C6, C7, C8A, C8B, C8G, C9, CD46,CD59, CFB, CFD, CFH, CFHR1, CFHR2, CFHR3, CFHR4, CFHR5,CFI, CFP, FCN3, ITGAM, MASP2, SERPING1, THBD.

14. List of gene panels used
• Hereditary hemophagocytic lymphohistiocytosis 10‐gene panel (N = 2
patients)
• AP3B2, BLOC1S6, PRF1, UNC13D, STX11, STXBP2, RAB27A, LYST, SH2D1A, XIAP.
• Rhabdomyolysis 91‐gene panel (N = 1 patient)
• ACAD9, ACADM, ACADVL, ACTA1, AGL, ALDOA, ANO5, B3GALNT2, B4GAT1, BAG3, CAPN3, CASQ1, CPT1A, CPT2, CRYAB, CTDP1, DAG1, DGUOK, DMD, DNA2, DNAJB6, DPM1, DPM2, DYSF, EMD, ENO3, ETFA, ETFB,
ETFDH, FHL1, FKRP, FLAD1, FLNC, G6PD, GAA, GBE1, GMPPB, GNE, GYG1, GYS1, HADHA, HADHB, HMBS, ISCU, ISPD, ITGA7, KBTBD13, KLHL40, LAMA2, LAMP2, LDB3, LDHA, LMNA, LPIN1, MEGF10, MICU1, MTM1,
MYOT, NEB, PFKM, PGAM2, PGK1, PGM1, PHKA1, PHKB, PNPLA2, POMGNT1, POMT1, POMT2, PYGM, RBCK1, RRM2B, RYR1, SGCA, SGCB, SGCD, SGCG, SIL1, SLC22A5, SLC25A20, SUCLA2, SUCLG1, TANGO2, TCAP,
TK2, TNNT1, TNPO3, TPM2, TPM3, TRIM32, FDX2.
• Blau syndrome (N = 4 patients)
• NOD2.
• Osteogenesis imprefecta AJCH 48‐gene panel (N = 1 patient)
• COL1A1, COL1A2, BMP1, CRTAP, FKBP10, P3H1, PLOD2, PPIB, SEC24D, SERPINH1, SPARC, TMEM38B, CREB3L1, IFITM5, MBTPS2, MESD3, SERPINF1, SP7, TENT5A, WNT1, LEPRE1, FAM64A, PLS3, ALPL, ANO5,
B3GAT3, B4GALT7, CLCN5, COL1A1, DMP1, FGF23, ENPP1, GNAS, GORAB, LMNA, LRP5, MAFB, MMP2, NBAS, NOTCH2, P4HB, PHEX, PLOD3, SLC34A3, TAPT1, TNFRSF11A, TNFRSF11B, XYLT2.
• Arthropathy panel (N = 2 patients; one patient had PRG4 sequencing
only)
• PRG4,WISP3.
• ADA2‐related disease (N = 1 patient)
• ADA2

15. WES (Whole exome sequencing)
• All known pathogenic variants in ClinVar/HGMD and novel
loss‐of‐function (LoF) variants in disease genes were
retained. In addition, segregation analysis was performed for
family‐based (trio, quad, quint) WES to identify dominant, de
novo, homozygous, and compound heterozygous variants

16. Cohort
• Our cohort consisted of 71 paediatric , median age: 8.5 years,
range: 0.88–18 years.
• 48% females, and 52% males.
• Most (68/71 or 96%) patients were Arab descendants, including
28 Emiratis (39%), 13 North African (Egypt, Algeria, Morocco)
Arabs (18%), 7 Syrians (10%), 6 Palestinians (8%), 6 Jordanians
(8%), 2 Lebanese (3%), and 2 Yemenis (3%).
• Consanguinity was self‐reported in 30% (21/71) of the families.

21. Implications of genetic diagnosis
1. Identification of genetic disease that differs from the
presumptive diagnosis. This changed the suggested treatment.
For example, siblings were treated for JIA , found to have
Progressive pseudo rheumatoid dysplasia (PPRD) which
doesn’t have known treatment.
2. An unexpected pathogenic variant in MEFV (p.A744S) was
detected in the heterozygous state in Patient mandating long
term follow up.
3. Patient presented with clinical picture of SLE supported by
serological and chemical tests. Found to have MEFV gene
which led to the diagnosis of FMF.

22. 4. Proper selection of treatment choice.
5. Stopping unnecessary immune suppressive treatments (these
medications are usually used for long durations)
6. Can explain the disease progress that does not fit the natural
history.
7. Confirming a diagnosis is important in monitoring for the
development of complications (e.g., a higher risk of secondary
amyloidosis in patients with FMF and TRAPS).

23. • ICU patient who had life‐threatening active bleeding due to
chronic refractory immune thrombocytopenia. She had No
response to several Platelets transfusion with no clear reason.
Genetictestingsolvedtheproblemandidentifiedthedefect!!
Couldbeusedtodevelopatreatment?

24. In summary
• Genomic testing in an evolving diagnostic tool that is important
for diagnosing and managing paediatric patients with a
spectrum of rheumatic disorders.
• More efforts are needed disseminate the culture of genetic
testing in diagnosing and managing patients.
• The genomic world is still evolving and more yet to be
discovered and more answers yet to be found.