1-6 Choice of Reliable - Dr.M Sha3rawy

8/14/2019 1-6 Choice of Reliable - Dr.M Sha3rawy

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Osteoporosis is a syndrome characterized by

a reduced bone mass such that there is an

increased risk of bone fracture. The hip, wrist

and spine are the most vulnerable.

Osteoporosis is due to due to low peak bone

mass and/or excessive bone loss.

Osteoporosis


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Type II or Senile Osteoporosis

It affects people 75 years old or more, with

women twice as likely to be affected. It ischaracterized by both cortical and trabecular

bone loss. Fractures may occur in all the

skeletal sites, but the pathognomonic

fracture for type II osteoporosis is the hip

fracture.


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Type III Osteoporosis or Secondary Osteoporosis

In 10% of women and 50% of men osteoporosis issecondary to other diseases or treatments.

* Amenorrhoeic athletes * Pregnancy

* Hyperprolactinemia * Lactation

* Hyperthyroidism * Alcohol intake

* Long-term corticosteroids therapy * Smoking

* Immobilization * Anorexia nervosa

* Malabsorption * Osteogenesis Imperfecta (Familial)

* Hypothyroidism (Iry) * Hypogonadism


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Calcium Regulating Hormones: PTH, l,25 dihydroxy Vit. D,

CT.

Other Hormones: Thyroid, Pituitary, Adrenal and Gonadal

Steroids.

Cytokines and Growth Factors: M-CSF, IL-1, IL-6, IL-11

control osteoclasts development.

TGF : local mediator of osteoblast - osteoclast coupling. IGFs I & II, FGFs, PDGFs: Influence osteoblastic activity.

PTH-RP, FGFs: Involved in cartilage differentiation.

Regulatory Mechanisms of Skeletal

Remodelling and Calcium Metabolism


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1. Measurement of BMD: assess risk of fracture.

2. Histomorphometry of bone biopsies: provide

information on the pathogenesis but it is invasive

method.

3. Calcium kinetic studies: provide information on the

rate of bone turnover and Ca++ absorption but it is

time consuming.

Radiological Assessment


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Provides Information on:

1) Pathogenesis.

2) Rate of bone turnover.

3) Monitoring antiresorptive therapy.

4) Identify fast bone losers at risk of hip fracture.

Biochemical Assessment


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Blood level correlates with histomorphometric and 47 Ca

measurements of bone formation.

Biomarkers of Bone Formation

B-ALP Isoenzyme present on osteoblast membrane,

its synthesis increases during osteoblastic

differentiation.

OC Synthesized by osteoblasts.

PICP and P1NP Present in bone and skin and other tissues

containing collagen.


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* Released only during bone resorption

Biomarkers of Bone Resorption

Bone tartarate resistant acidphosphatase (TRACP)

Present in osteoclast and other macrophages. Serumlevel correlates with histomorphometry.

OHPr Present in all collagen molecules, released during

both bone formation and bone resorption.

Galactosy1 hydroxylysine

(GHYL)*

Present only in collagen; 5/7 times more abundant in

type I collagen of bone than in type 1 collagen ofskin.

Pyridinium cross-links (Pyr. &

DPyr)*

Non-reducible cross-links that form among 2

hydroxylysine residues on the collagen telopeptides

and one lysine or hydroxylysine residue on the helix protion of an adjacent molecule after deposition

of collagen in matrix DPyr is present mainly in bone.

ICTP and INTP (NTX)* Present in all tissues containing type 1 collagen


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Serum IR BSP

Bone Sialoprotein (BSP) is a heavily glycosylated and

phosphorylated protein that accounts for 5-10% of the non-

collagenous proteins of the bone extracellular matrix. BSP

plays an important role in cell-matrix adhesion processes

and in the supramolecular organization of the extracellular

matrix of mineralized tissues. BSP appears to be a sensitive marker of bone turnover and

its serum levels reflects processes related to bone

resorption (Seible et al., 1996).

Biomarkers of Bone Resorption Cont'd


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Closer concordance of BMD in monozygotic as

opposed to dizygotic twins (Smith 1993).

Reduced BMD in daughters of osteoporoticwomen when compared with control subjects

(Fotino et al., 1977)

Family history of osteoporosis predicts BMD(Soroko et al., 1994).

Evidence In Favour of A Genetic Contribution

to Osteoporosis


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An association between VDR genotypes and

serum Vit. D response gene Osteocalcin

(Lander and Schork, 1994).

A strong association between VDR

polymorphisms and BMD (Morrison et al., 1994).

Candidate Genes for Osteoporosis


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Estrogen Receptor Gene ER Gene

An osteoporotic phenotype has been noted in a

man with a coding region mutation of the ER

gene (Smith et al., 1994).

Intronic RELP and T/A repeat polymorphism of

the ER gene has been associated with BMD

(Kobayashi et al., 1996).


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Mutations affecting coding unions of the genes give

rise to a severe osteoporotic phenotype (osteogenesis

imperfecta).

G/T polymorphism at COLI Al predicts bone

mass (Granl et al., 1996).

G/T heterozygotes (Ss) have significantly lower BMD at

the lumber spine than G/G homozygotes (SS) and BMD

is still lower in T/T homozygotes (ss).

Collagen Type I Genes (COL1) Al, COLI A2)


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Genomic DNA extraction can be performed on a venous blood

sample to study genetic polymorphism which are likely to be of

value as indicators of osteoporotic fracture risk in clinical

practice.

1) VDR polymorphism.

2) COLI Al SP1 polymorphism.

These genetic markers may be used - in combination with

existing techniques - to improve the identifications of patients

at risk of osteoporosis before the condition has became

established.

Genetic Biomarkers of Bone Turnover


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Unfavorable Ss and ss genotypes are over

represented in osteoporotic vertebral fracture

patients with a calculated relative risk of fracture of

about 3 in individuals who carry the "s" allele as

compared with "SS" homozygotes. The "s" allele

may act as a marker for increased age related bone

loss rather than peak bone mass.


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Choice of Reliable Biochemical Markersfor the Assessment of Bone Turnover

in Postmenopausal Osteoporosis


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Aim of Work

This study was undertaken to asses bone

turnover in PMO by a battery of 15

biochemical markers of bone formation and

of bone resorption in order to select the most

reliable markers.


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Markers of Bone Formation

Serum biomarker Method Company Controls

Mean +SD

PMO mean

+SD

Significant

changes

Total OC (ng/ml) IRMA CIS 20.6+5.2 32.3+8.5 + 57%

B-ALP (ng/ml) IRMA Hybritech 9.6+4 18.3+5.7 + 91%

PICP (ng/ml) RIA Orion Diag 100+20 120+26 NS

CT (ng/ml) RIA DPC 15.2+12.9 12+6 NS

PTH-C (ng/ml) RIA Immunonuclear 1.8+4.5 0.46+0.2 NS

PTH-M (pmol/L) RIA Immunonuclear 80.9+50.1 64.5+26.8 NS

VIT D3 (mg/ml) RIA Immunonuclear 16.3+4.7 15.4+4.8 NS

Ca++ (mg/dl) Colorimetric Bioanalytics 8.7+0.8 9.2+1.7 NS

P (mg/dl) Colorimetric Bioanalytics 4.1+0.7 4.2+1.4 NS

Intraassay CV : 1.6-7.8%, Interassay CV: 1.1-9.2%


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Markers of Bone Resorption

Biomarker Method Company Controls

Mean +SD

PMO mean

+SD

Significant

changes

u Pyr (nmol/mmol Cr) ELISA Metra 35.6+10 48+11.2 + 35%

u D Pyr (nmol/mmol Cr) ELISA Metra 5.8+1 10+4 + 72%

u. NTX (nmol/mmol Cr) ELISA Ostex 30.8+14.3 90.3+36.4 + 193%

s. ICTP (ng/ml) RIA Orion 4.2+1 4+0.9 NS

u. cAMP (nmol/mg Cr) RIA Immunonuclear 25+22.3 21.7+19.2 NS

u. OHPr (mg/mg Cr) Colorimetric ----- 0.02+0.02 0.02+0.01 NS

Intraassay CV : 2.8-8.6%, Interassay CV: 7.1-10%


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T-score = X-M / SD

Calculated Uncoupling Status = 4.19-9.25 =

-5.06

T* (z) Score of Biomarkers of Bone

Turnover in PMO

Bone formation T-score Bone resorption T-score

OC 2.25+2 Pyr 1.2+1.1

B-ALP 2.2+1.9 D Pyr 4.2+3.2

PICP 0.98+1.0 NTX 4.2+2.6

Vit D3 -0.2+0.3 ICTP -0.2+0.2

PTH-M -0.33+0.3 cAMP -0.15+0.2

PTH-C -0.3+0.4 OHPr 0.0

CT -0.4+0.5 - -

Net T-score 4.19 Net T-score 9.25


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T-Score of Biomarkers of Bone

Turnover in PMO

The calculated uncoupling status of 12

biomarkers of bone formation and bone

resorption equals to - 5.0. On the other hand, thecalculated value of the 4 most reliable

biomarkers of bone formation (OC & B-ALP) and

bone resorption (NTX and DPyr) equals to -4.0.This difference does not necessitate the assay

of 12 instead of 4 biomarkers.


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Bone Turnover in PMO was significantly

higher than in healthy PM women.

The most reliable markers which are able to

discriminate between slow and fast bone losersin PM women were B-ALP and OC for

assessment of bone formation and NTX and

DPyr for assessment of bone resorption. These

4 combined assays may be able to augment or

replace bone densitometry for monitoring

antiresorptive in PMO.

CONCLUSION


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Markers of Bone Formation (Osteoblastic Activity):

Ostase (B-ALP): ............ ng/ml (NV-1 -15)

Osteocalcin (GLA-Protein): ....... ng/ml (NV-8-28).

Markers of Bone Resorption (Osteoclastic activity):

NTX (Osteomark) ............ mmol/mmol Cr (NV-up to 58)

Deoxypyridmollns (Pyr) mmol/mmol Cr (N-0.4-6.4)

Calculated uncoupling statues of T-scores:

- Normal : below-0.8

- Slow bone losers : 0.8 to 3.0

- Fast bone losers : above -3.0


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Early detection of Osteoporosls

Selection of suitable patients for HRT

Monitoring anti-resorptive therapy

Diagnosis of fast bone loser at high risk of bone fracture.

Monitoring bone metabolism in patient with:

- Hypothyroidism.

- Hyperthyroidism.

- CRF.- GH deficiency.

Monitoring bone metabolism in patients on long term

corticosteroids or NSAID therapy.

Indications of Bone Markers Assays


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Activated T Cells Mediated Bone Loss

through the triangle

RANKL / RANK/OPG


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Activated T-cells can increase the number

of osteoclasts and reduce BMD both in

vitro and in vivo (Kong, et al, 1999). This

may explain the association of bone loss

with leukemia or infections.


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TNF Ligand family member: Receptor

Activator of Neuclear Factor-kB Ligand

(RANKL) or Osteoprotegerin Ligand (OPGL)

and its receptor (RANK and soluble receptor

Osteoprotegerin (OPG) has established a

novel paradigm of osteclast biology.


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RANKL, RANK and OPG constitute the 3 essential

regulatory components of ostecldast formation, fusion,

survival, activation and apoptosis (Hofbouer et al,

2000).

- RANK-ODF (Osteoclast differentiation factor).

- RANK-ODAR (Osteoclast differentiation activation

receptor).

- OPG-OCIF (Osteoclastogenesis Inhibitory factor).


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RANKL increases the pool of active

osteoclast by activating its specific receptor

RANK located on osteoclastic cells, thus,

increasing bone resorption.

OPG neutralizes RANKL and has opposite

effects.


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RANKL and OPG are produced by bone marrow

derived stromal cells and osteoblasts and are

regulated by various calcitropic cytokinei,

hormones and drugs. Abnormalities in RANKL/OPG

ratio have been implicated in different metabolic

bone diseases characterized by increased

osteoclastic differentiation, activation and

enhanced bone resorption.


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Among the factors that increases RANKL mRNA

expression in osteoblastic cells are the

prolnflammatory cytokines IL-1, IL-6, IL-11 and

TNF- (Yasuda et al, 1998 and Hofbauer et al,1999). Inflammatory lesions of bone are

characterized by abundant osteoclast

proliferation.


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TNF- is a potent osteoclastogenic agent andappears to mediate orthopedic implant loosening

(Merkel et al, 1999). TNF- stimulates osteoblasticcells to express RANKL which in turn prompt

macrophages to become osteoclasts. Consistent

with this hypothesis, systemic adminstration of OPG

blocks osteoclastogenesis in experimental arthritis,

a situation in which there are abundant amounts of

TNF- (Kong et al, 1999).


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Products of breast cancer cells (PTH rP, IL-6, IL-

11 and cyclooxygenase-2 generated prostanoids)

promote RANKL formation by acting on residentosteoblasts and/or stromal cells (Thomas et al,

1999) The release of growth factors especially

TGFp can influence the growth of tumor cells andtheir production of bone-resorbing cytokines (Vin

et al, 1999).


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Rheumatoid arthritis is characterized by destruction

of articular cartilage and by excessive subchondrial

osteoclastic bone resorption (Romas et al, 2000). In

the inflammatory state, macrophages, which

differentiate into osteoclasts, accumulate in the

rheumatoid synovial membrane where there are

many osteoclastogenic cytokines including IL, IL-6,

IL-11, IL-13, IL-17 (Kotake et al, 1999) and PTHrP.


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Rheumatoid synovial fibroblasts produce

RANKL (Romas et al. 2000) and T-cells

producing RANKL have been shown to promote

osteoclast formation without the participation of

other cells (Norwood et al, 1999).


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On the other hand OPG production is stimulated by

E2 (Saika et al, 1999), calcium cation (Yasuda et al,

1998) and bone morphogenetic protein-2 (Hofbauer

et al, 1998).

OPG production is decreased by PGE2 (Brandstrom

et al, 1998), glucocorticoids (Vidal et al, 1998), 1 ,25 (OH)2 D3 (Norwood et al, 1998), estrogen receptor

antagonist (Hofbauer et al, 1999) and PTH (Lee &

Lorenzo, 1999).


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Therefore RANKL/OPG, are the key agonist /

antagonist cytokine system that regulate osteoclast

biology including differentiation, fusion, survival,activation and apoptosis. RANKL increases the pool

of active osteoclasts by activating its specific

receptor RANKL located on osteoclastic cells, thus

increasing bone resorption, whereas OPG which

neutralizes RANKL, has opposite effects.


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PTH Glucocorticoids Vit D3

E2PRL

Hypothyroidism

Decreased OPG

Abnormal RANKL/OPG Ratio

Decreased Osteoblastic Activity

Increased Bone Resorption


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Infections / cancer

T-cell activation Increased osteoclastogenic

Cytokines IL-6, IL-11, TNF-

PE

Increased osteoclast

Activating growth factors(TGF- )

PGE2 Increased RANKL PTH, PTHrP Abnormal RANKL/OPG ratio

Increased osteoclastic activity

Increased bone resorption


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Shaarawy M, Zaki S, Shehata H. Circulating levels

of osteoclast activating cytokines, interleukin-11

and transforming growth factor B2 as valuable

biomarkers for the assessment of bone turnover

and monitoring antiresorptive therapy in

postmenopausal osteoporosis. Clin. Lab

(Germany) 2003; 40: 625-636.

Further Readings


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Shaarawy M, Abassi AF, Hassan H, Salem ME.

The relationship between serum leptin

concentrations, bone mineral density and

biochemical markers of bone turnover in

postmenopausal osteoporosis. Fertil Steril, 2003;

79: 919-924.


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Shaarawy M, Hasan M. Serum bone slaloprotein,

a reliable biomarker of bone resorptlon In

diagnosis and monitoring treatment of

postmenopausal osteoporosis. The Scandinivian

Journal of Clinical and Laboratory Investigation

2001; 61: 513-522.


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Shaarawy M, Shaltout F, Idris O, Sheiba M, Wali

M. Circulating levels of insulin-like growth factor-

1 and insulin-like growth factor binding protein -3

as valuable markers in the assessment of bone

remodeling and monitoring antiresorptive

therapies in postmenopausal osteoporosis. Arab

J. Lab Med 2002; 28(1): 79-104.


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Shaarawy M, EI-Mallah SY, Hassan HE, Aref

At. Choice of reliable biochemical markers for

assessment of bone remodeling in

postmenopausal osteoporosis. J. North

American Menopause Society 1997; 4: 212-218.


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Shaarawy M, EI-Dawakhly AS, Mosaad M, El-

Sadek M.M Biomarkers of bone turnover and

bone mineral density in hyperprolactinemic

amenorrheic women. Clin. Chem Lab Med

(Eur) 1999; 37 (4): 433-438.


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Darwish NA, Shaarawy M, Ezzat R, EI-Kafas H.

Hormonal and biochemical changes in

postmenopausal age related bone loss. A

biochemical profile for the differential diagnosis

of senile and postmenopausal osteoporosis and

assessment of the severity of osteoporotic

changes. Egypt Soc Obstet Gynecol 1988; 14 (1):

103-111.


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Shaarawy M, EI-Mallah SY, Shaltout F, Abbasy A.

Serum osteocalcin Gla-protein levels in senile

and postmenopausal osteoporosis. Arab J. Lab

Med. 1990; 16(1): 1-10.


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1-6 Choice of Reliable - Dr.M Sha3rawy

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