El lunes y martes 20 y 21 de noviembre coordinamos un simposio internacional en la Fundación Ramón Areces, sobre los defectos del transporte de aminoácidos.

1. Immune (and other) alterations in
patients with lysinuric protein
intolerance (LPI)
Juha Mykkänen
Research Centre of Applied and Preventive Cardiovascular Medicine
University of Turku
Finland
Amino Acid Transport defects symposium
Madrid, November 20-21, 2017

2. Background
• First described by Perheentupa and Visakorpi 1965
• Autosomal recessive, incidence in Finland 1:60 000
• ~ 50 patients in Finland
• All Finnish patients share the same homozygous
mutation in SLC7A7 gene – Founder effect
• Carrier frequency in Oulu 1:91 vs. Helsinki 1:194
Birth places of LPI patients’
grandparents
Oulu
Helsinki
Finnish disease heritage

3. LPI: basolateral transport defect of y+LAT1 in small
intestine and kidneys
Finnish founder mutation in y+LAT1
- Splice site, premature stop codon
S. Bröer et al. Biochm. Soc. Trans. 2005;33:233-236
y+LAT1/4F2hc
Lys, Arg, Orn

4. Symptoms, laboratory findings

5. Symptoms, laboratory findings Treatment
Growth hormone therapy
Low-protein diet
- children 1.0 g/kg/day
- adults 0.8 g/kg/day
L-citrulline
Lysine-hydrochloride
Sodium-benzoate/-phenylbutyr
Statins
Carnitine
Vitamins, minerals, calcium
Varicella, pneumococci and
influenza vaccinations

6. J. Kurko 2016, Modified from Sebastio et al. 2011 and Ogier de Baulny et al. 2012.
Current model of LPI patophysiology
Ornithine
Arginine
Citrulline
Ira = intestine-
renal axis
CKD = chronic
kidney disease
PAP = pulmonary
alveolar
proteinosis
HLH =
Hemophagocytic
lymphohistiocyto
sis
MAS =
macrophage
activation
syndrome

7. • 13 LPI patients, 10 controls
• Whole-blood samples (PAXgene)
• Illumina genome-wide array
• qPCR-validation in larger patient population (n=36) and more
specific cell types (PBMC, reticulocytes)
Maaria Johanna

8. • Links to immune response, liver
and kidney
GO (gene ontology) -analysis
IPA (ingenuity pathways analysis)

9. Expression (qPCR) of amino acid transporter genes in various cell types of LPI patients
Whole blood cells PBMCs MDMs Reticulocytes
Gene
symbol
log2 FCa P log2 FCa P log2 FCa P log2 FCa P
SLC1A5 1.86 < 0.001 0.00 NS -0.14 NS 1.10 < 0.05
SLC7A1 0.73 < 0.001 -0.12 NS -0.01 NS 0.08 NS
SLC7A2 ND ND ND ND
SLC7A5 1.79 < 0.001 0.48 NS -0.52 NS 1.20 < 0.01
SLC7A6 -0.79 < 0.05 -0.43 < 0.01 -0.21 NS -0.01 NS
SLC7A7 -3.05 < 0.001 -2.81
7.83 x 10-
11 -4.72
7.20 x 10-
29 -1.46 < 0.05
SLC3A2 0.04 NS 0.18 NS -0.17 NS 0.27 NS
a FC = fold change
NS = not significant, ND = not detectable, MDM = monocyte-derived macrophage

10. Expression (qPCR) of immune genes in various cell types of LPI patients
Whole blood cells PBMCs
Gene symbol log2 FCa P log2 FCa P
IL1RN NA 0.77 < 0.05
IL1B -1.36 < 0.001 1.79 < 0.01
CXCL8 -1.58 < 0.001 3.74 6.56 x 10-5
CXCR2 -1.32 < 0.001 -0.93 < 0.001
IL12B NA -0.3 NS
IL18RAP -1.98 1.17 x 10-6 -1.38 7.94 x 10-5
TNF NA 0.19 NS
NAMPT -2.09 6.29 x 10-6 1.56 < 0.001
IFI27 4.58 5.41 x 10-6 3.78 < 0.001
LAMP2 NA 0.43 < 0.05
a FC = fold change, NA = not available, NS = not significant

11. Expression (qPCR) of immune genes in various cell types of LPI patients
Circulating CXCL8 in plasma
Whole blood cells PBMCs
Gene symbol log2 FCa P log2 FCa P
IL1RN NA 0.77 < 0.05
IL1B -1.36 < 0.001 1.79 < 0.01
CXCL8 -1.58 < 0.001 3.74 6.56 x 10-5
CXCR2 -1.32 < 0.001 -0.93 < 0.001
IL12B NA -0.3 NS
IL18RAP -1.98 1.17 x 10-6 -1.38 7.94 x 10-5
TNF NA 0.19 NS
NAMPT -2.09 6.29 x 10-6 1.56 < 0.001
IFI27 4.58 5.41 x 10-6 3.78 < 0.001
LAMP2 NA 0.43 < 0.05
a FC = fold change, NA = not available, NS = not significant

12. Whole blood cells Reticulocytes
Gene symbol log2 FCa P log2 FCa P
ALAS2 1.75 3.58 x 10-5 1.12 < 0.01
BLVRB 2.80 7.94 x 10-11 0.69 < 0.05
BSG 2.29 7.44 x 10-9 1.09 < 0.01
CAI 4.26 6.29 x 10-10 2.46 1.36 x 10-6
EPB42 2.76 4.78 x 10-9 1.67 3.24 x 10-5
ERAF 4.16 2.60 x 10-12 2.99 3.41 x 10-7
FECH 1.72 1.32 x 10-5 0.04 NS
HBQ1 2.34 5.03 x 10-7 0.73 < 0.05
HEMGN 0.90 < 0.05 -1.10 < 0.01
HRI 1.11 < 0.001 0.96 < 0.05
MSCP 1.48 9.39 x 10-5 0.81 < 0.05
SELENBP 2.77 1.20 x 10-7 1.26 < 0.001
SLC2A1 2.12 1.16 x 10-8 2.80 1.48 x 10-6
SLC4A1 2.19 4.03 x 10-7 1.64 < 0.01
IFI27 4.58 5.41 x 10-6 4.82 5.94 x 10-5
a FC = fold change, NS = not significant
Expression (qPCR) of reticulocyte-specific genes in various cell types of LPI patients

13. Whole blood cells Reticulocytes
Gene symbol log2 FCa P log2 FCa P
ALAS2 1.75 3.58 x 10-5 1.12 < 0.01
BLVRB 2.80 7.94 x 10-11 0.69 < 0.05
BSG 2.29 7.44 x 10-9 1.09 < 0.01
CAI 4.26 6.29 x 10-10 2.46 1.36 x 10-6
EPB42 2.76 4.78 x 10-9 1.67 3.24 x 10-5
ERAF 4.16 2.60 x 10-12 2.99 3.41 x 10-7
FECH 1.72 1.32 x 10-5 0.04 NS
HBQ1 2.34 5.03 x 10-7 0.73 < 0.05
HEMGN 0.90 < 0.05 -1.10 < 0.01
HRI 1.11 < 0.001 0.96 < 0.05
MSCP 1.48 9.39 x 10-5 0.81 < 0.05
SELENBP 2.77 1.20 x 10-7 1.26 < 0.001
SLC2A1 2.12 1.16 x 10-8 2.80 1.48 x 10-6
SLC4A1 2.19 4.03 x 10-7 1.64 < 0.01
IFI27 4.58 5.41 x 10-6 4.82 5.94 x 10-5
a FC = fold change, NS = not significant
Expression (qPCR) of reticulocyte-specific genes in various cell types of LPI patients
Increased reticylocytosis in response to haemolytic anaemia.
Cause or effect of the abnormal erythrocyte morphology?

14. Innate/non-specific Adaptive/acquired
Anatomical
components
Skin, respiratory tract,
gastrointestinal tract
Bone marrow, thymus,
mucosal-associated lymphoid
tissue, lymph node
Cells Monocytes, macrophages,
dendritic cells, natural killer
cells, neutrophils, mast cells,
eosinophils, basophils
T and B lymphocytes
Proteins Cytokines, complements,
collectins and lysozymes
Immunoglobulins
Receptors Pattern recognition receptors
(encoded in a germline)
Antigen-specific receptors
(rearranged during
development, somatic
recombination)
Distribution of
receptors
Non-clonal Clonal
Targets of recognition Conserved molecular patterns
(LPS, LTA, glycans)
Details of molecular structure
(proteins, peptides,
carbohydrates)
Specificity Non-specific activity Specific (molecular) activity
Onset of response Immediate (hours) Delayed (days)
Memory No Yes
Self-discrimination Yes, but indiscriminate tissue
damage can occur
Yes, but it is imperfect
(autoimmunity)
LPS = lipopolysaccharide, LTA = lipoteichoic acid
Modified from Janeway and Medzhitov, 2002, Li et al., 2007.
TLR
TLR
adapter
TLR location Ligand examples
TLR2/TLR1 MyD88 Cell surface
triacyl lipopeptides,
Pam3CSK4 (synthetic)
TLR2/TLR6 MyD88 Cell surface
diacyl lipopeptides, LTA,
Zymosan
TLR3 TRIF Endolysosome
dsRNA (viral), poly(I:C)
(synthetic)
TLR4
MyD88/TR
IF
Cell surface/
endosome
LPS (bacterial), HSP 60,
70
and fibrinogen
(endogenous)
TLR5 MyD88 Cell surface Flagellins (bacterial)
TLR7 MyD88 Endolysosome
ssRNA (viral), IAQ
(synthetic)
TLR8 MyD88 Endolysosome
ssRNA (viral), IAQ
(synthetic)
TLR9 MyD88 Endolysosome CpG DNA (bacterial/viral)
TLR10/
TLR2?
MyD88? Cell surface bacterial and viral
LPI immunological studies – role of innate immunity

15. • 23 LPI patients, 15 controls
• 3 TLR-signaling routes studied:
• TLR2/TLR1 (Pam3CSK4)
• TLR4 (LPS)
• TLR9 (CpG DNA)
• Gene expression of 39 genes (qPCR)
• Expression of 26 cytokines/chemokines
(Luminex)
• NO (nitrite) concentrations in 0h cell
culture medium and plasma

16. Expression of SLC7A7 is induced (~2-fold) by TLR9 activation
qPCR results

17. • Plasma NO, CXCL9 and CXCL10
had inverse correlation with
kidney function (eGFR)
Cytokines in cell culture medium
Cytokines in plasma
NO in 0h cell culture medium and plasma
NOS2 undetectable in differentiated
macrophages by qPCR
CXCL8 CXCL9 CXCL10

18. • Plasma NO, CXCL9 and CXCL10
had inverse correlation with
kidney function (eGFR)
• Some LPI patients may have a
systemic inflammatory state
• In LPI patients with renal
dysfunction inflammation may
attract leukocytes to the injured
kidney to perpetuate the
Cytokines in cell culture medium
Cytokines in plasma
NO in 0h cell culture medium and plasma
NOS2 undetectable in differentiated
macrophages by qPCR
CXCL8 CXCL9 CXCL10

19. • 26 LPI-patients, 19 controls, plasma samples
• Targeted analysis of 42 amino acids with iTRAQ and liquid chromatography
coupled to tandem mass spectrometry (LC-MS/MS)
• Global polar metabolites with two-dimensional gas chromatography coupled
to time-of-flight mass spectrometry (GC×GC-TOFMS)
• Global lipids with ultra-performance liquid chromatography coupled to
quadrupole time-of-flight mass spectrometry (UPLC-Q-TOFMS)

20. Essential aa
Non-essential aa

21. Correlations of significant amino acids, medications, clinical
laboratory values and glomerular filtration rate (eGFR)
Negative associations with GFR
- Homocitrulline
- BAIBA
- NO
- Statin medication
- Cationic amino acids
Positive associations with GFR
- Carninite
- Serine

22. Unsupervised hierarchical clustering of significant metabolites (n=58, 22 down, 36 up in LPI)

23. Unsupervised hierarchical clustering of significant metabolites (n=58, 22 down, 36 up in LPI)

24. eGFR

25. • Gut microbial metabolism of sugars
(FDCA, galactaric acid) and amino
acids (HPA, IAA)
• Oxidative stress (threonic acid)
• Browning of white fat (BAIBA)
LPI CKD metabolites

26. • Triglycerides high
• Certain phosphatidylchlolines low
Global lipidomics, 198 up, 46 down
Data reduction by clustering

27. Correlations of lipid clusters, medications, clinical laboratory
values and glomerular filtration rate (eGFR)
Citrulline supplementation may
improve kidney function by inducing
lipolysis and glycerol oxidation
Negative correlation of lipid clusters
including long-chain triglycerides (LC6,
LC8) with eGFR
- eGFR has no correlation with clinical
laboratory lipids, only with specific
subclasses
Lipid metabolism in the liver, normally
balanced between fatty acid and TG
synthesis by lipogenesis (energy intake)
and degradation by lipolysis and
further fatty acid β-oxidation (energy
combustion), is disrupted in LPI

28. Modified model of LPI pathogenesis
J. Kurko 2016

29. LPI-team:
Johanna Kurko
Maaria Tringham
Harri Niinikoski
Laura Tanner
Kirsti Näntö-Salonen
Olli Simell, professor emeritus
Thank you!
Transcriptomics:
Johannes Tuikkala
Olli Nevalainen
Innate immunity:
Mari Vähä-Mäkilä
Sari Paavanen-Huhtala
Plasma omics:
Anu Olkku
Heli Nygren
Päivi Pöhö
Niina Lietzen
Ismo Mattila
Tuulia Hyötyläinen
Matej Oresic
Statistics:
Maiju Saarinen