Received 1 April 1998 Accepted 29 October 1998
 

INTRODUCTION

It has been previously suggested that high levels of cation metals such a manganese may interact with the CNS prion protein (PrP) and play a role in the pathogenesis of sporadic forms of transmissible spongiform encephalopathy (TSE) (1,2).
Analyses of ecosystems supporting isolated, well defined clusters of sporadic TSE in Iceland, Colorado and Slovakia demonstrate high concentrations of the free radical generating divalent cation, manganese (Mn), as well as marked deficiencies of the radical scavenger enzyme cofactors; Cu, Zn, Fe, Se and the elements Mg/P/Na. The findings of high levels of Mn in TSE ecosystems may not necessarily indicate any direct relationship between Mn overloading and the aetiology of TSE. It could merely reflect some indirect association between the two; eg, where a further 'third party' common environmental factor which promotes the accumulation of Mn in plant material may also promote the survival of 'agent X' which causes TSE.
However, various other research studies indicate that the results of this survey may indeed demonstrate a direct aetiological association between Mn exposure and TSEs. For instance, close similarities exist between the pathological/clinical profile of TSEs and the Mn induced delayed psycho-neurodegenerative syndrome found in Mn miners (3,4) where the key idiosyncratic CNS pathological features of TSE (5), such as the presence of amyloid plaques and fibrils, are common to both conditions (6). Furthermore, 1999 pilot studies conducted by Dr David Brown of the Dept of Biochemistry, Cambridge University, UK, have demonstrated that the divalent cations, Mn and Nickel, will both bind to recombinant PfP and refold the protein into a protease resistant, misfolded isoform. Protease-resistant PrP represents the foremost key feature that hallmarks the pathology of TSE diseased brain (5).
        A novel aetiological hypothesis for TSEs is compiled from the data amassed in this pioneer study of TSE ecosystems. It proposes that the trivalent species of Mn cation serves as the all important 'infectious' transmissible agent in TSEs.
        Mn is a divalent cation, and, much like other divalent species such as Cu and Fe, Mn can perform a dual role in biological systems; as a pro oxidant when freely 'available' at high concentrations and as an antioxidant when conjugated onto its respective scavenger enzyme, Mn superoxide dismutase (Mn SOD) (3,4). During the resting stages of the enzymic cycle, MnSOD acts as a safe 'depot' for Mn3+, thus protecting tissues against the potential onslaught of its pro-oxidant activities (3,4).
        It is proposed that sporadic TSEs with develop in defective MnSOD/PrP genotypes who are chronically dependent on foodchains that are characterised by two abnormal coexisting factors; high levels of the divalent cation Mn and deficiencies of other metals Cu/Zn/Fe/Se which serve as scavenger enzyme co factors in biological systems.(NB; Cu, Fe and P deficiencies in the external food chain would also promote the excessive absorption of Mn across the gut barrier (3,4).
        Cu deficient ecosystems generally conform to a seasonal Cu cycle that is characterised by a ten month period of Cu-starvation in vegetation, followed by an ephemeral 20 fold burst of Cu availability during August (8), which, in turn, mediates an ephemeral rise in levels of the Cu-glycoprotein 'ceruloplasmin' in mammals thriving off these foodchains (8). Such an abrupt increase in ceruloplasmin turn over could subsequently oxidise a greater proportion of the excess of Mn2+ into its lethal Mn3+ species (7) - particularly likely to occur in ecosystems deficient in ceruloplasmin's normal oxidative target, Fe2+. Mn2+/Mn3+ are recognized to concentrate exclusively within the CNS during contexts of Mn overloading (7), where excesses of 'available' Mn2+/Mn3+ can persist for up to a year (7). CNS Mn accumulation can result from intranasal intake of airborn concentrations of Mn transported via the olfactory neurones (9) as well as in the gastrointestinal route (3,4,7). Genotypes deficient in MnSOD activity would be less able to provide 'sink' storage for the excess of Mn, and would therefore be more susceptible to the ravages of Mn3+ induced chain reactions of oxidant mediated neurodegeneration (7,10,11); particularly prone to proliferation whilst supplies of Cu, Fe, Zn, Se within the CNS are depleted - metals required as co factors in the major radical scavenger enzyme/antioxidant groups; superoxide dismutases 1/2 (SOD 1/2), glutathione peroxidase, catalases and the antioxidant vitamin E (10).
 
TSEs and the misfolded metallo-glycoprotein, prion protein
 
Metalloproteins require specific complementary metals which assist in their folding, catalytic and/or metabolic activities (12). Alternative ‘foreign’ metals can sometimes substitute for the correct metal partner during periods of deficiency. For instance, Mn2+ or Fe2+ can also ligate onto the nitrogen of the histidine imidazole rings of certain Cu metalloproteins (12), resulting in the formation of misfolded isoforms which can no longer perform their correct metabolic functions.
        TSEs are considered to result from the accumulation of an abnormal protease resistant misfolded isoform of a nerve membrane metalloglycoprotein called prion protein (PrP) (5). PrP is largely expressed in the CNS and lymphatic systems (5).
        It is proposed that TSE pathogenesis is initiated (Fig. 1) once Mn2+ or Mn3+ substitutes for Cu at the ‘vacated’ histidine sites of Cu domains on PrP (15) and other cuproproteins such as the beta amyloid precursor protein. This could occur during periods of Cu deficiency, when PrP subsequently looses its correct conformation, ‘metamorphosing’ into a misfolded PrP-foreign transition metal complex, whereby Mn2+, or its oxidised Mn3+ species, serves as the ‘so called’ infectious transmissible agent whose potentially lethal auto-oxidative capacity (7,11) is carried along with PrP like a ‘trojan horse’ until the introduction of oxygen re-activates its latent oxidative capacity. At this point Mn3+ initiates a more aggressive auto-oxidative cascade of free radical chain reaction, involving the auto-oxidation of dopamine, serotonin and adrenaline; it is recognised that Mn3+ readily oxidises these catecholamines (10,7,11) forming 6-hydroxy-dopamine, etc, which, in turn, oxidise more rapidly, forming quinones and superoxide/hydroxyl radicals which modify the catecholamine terminals, which could theoretically modify various amino acids on PrP and other membrane proteins. Such radical chain reactions would be prone to proliferate in mammals living in environments that are depleted in Cu, Fe, Zn, Se. Such deficiencies cause a down regulation in the turnover of the SOD, catalase, peroxidase and vitamin E scavengers (10).).

Fig. 1   The multifactorial aetiological template underpinning the pathogenesis of sporadic TSEs, where an Mn3+ initiated chain reaction of auto oxidation invokes a multi site radical attack on PrP and other CNS membrane/cytoskeletal proteins.

        The pathogenic scenario involving the cycling of the stable Mn2+ and Mn3+ species can be likened to the redox cycling of the paraquat herbicide molecule and its role in initiating a Parkinsons-like pathogenesis (10,13,14,16). Alternating double bonds and ‘resonance energy’ within paraquat provides a stable ‘dormant’ radical which auto oxidises once oxygen is introduced. After reduction within the cell it reacts with oxygen to generate the lethal superoxide radical.(17)
Mn is also recognised to activate some species of lectin, such as phytohemagglutinins and concanavalin A (4), where high levels of free Mn can accelerate the normal rate of concanavalin A interaction with cell surface glycoproteins, such as PrP. Interestingly, the action of concanavalin A and phytohemagglutins mediates a 3.5 fold increase in the surface abundance of PrP (18). Furthermore, increases in both the surface expression of PrP and CNS membrane receptor capping with concanavalin A are consistently recorded in the early stages of the TSE disease process (19), suggesting that an excess of available Mn in the CNS could putatively perform a key role (via lectin activation) in initiating these facets of TSE pathogenesis.
 
CU CHELATING CHEMICALS INDUCE SPONGIFORM ENCEPHALOPATHIES
 
Cuprizone, neocuproine, mercaptoethanol, dithiophosphates and triethyltin are ‘true’ Cu chelating chemicals (20-22) which deplete Cu supplies in the CNS producing a ‘non-transmissible’, reversible type of spongiform encephalopathy. Cuprizone was actually utilised as a research tool for inducing a scrapie-like spongiosis in mice at Compton laboratories during the 1970s (23). CNS Cu deficiency could therefore represent one of the key prerequisites underlying TSE pathogenesis - albeit one which fails to account for the transmissible facet of TSEs.
        On the other hand, treatment with the ‘pseudo’ types of Cu chelating chemical such as diethyldithiocarbamate (DEDTC) (24) which chelate and redistribute Cu around the body rather than chelating and excreting it, do not produce spongiform encephalopathy (25); Allain et al. (24) treated rats with DEDTC which resulted in a 77% increase of Cu levels in the brain. Furthermore, DEDTC redistributes Cu into regions of the CNS that do not normally exhibit Cu binding ligands, thereby depositing free Cu in the extracellular space so it can initiate lipid peroxidation and chain reactions of hydroxyl and Cu 3 radical formation (10). Exposures to DEDTC and its parent compound sulfiram has been associated with the development of Parkinson’s disease and other extrapyramidal disorders (24, 26-28), supporting the proposal that CNS Cu deficiency rather than CNS Cu overloading is associated with TSE aetiology.
 
Is CNS Cu deficiency a prerequisite for TSEs?
 
Certain facets of TSE pathogenesis, such as tissue increase of Fe store, found as Ferritin (29), indicate a state of Cu/Fe deficiency.
        Furthermore, Lung tissues of copper deficient chicks have demonstrated abnormal variations in the concentration of various types of glycoaminoglycans (30). The possibility of an ‘in vivo’ metabolic relationship between PrP reduction within the cell, it reacts with oxygen to generate the lethal superoxide radical (17) and the glycoaminoglycans becomes evident after studying the TSE disease process (5); where concentrations of the sulphated glycoaminoglycans are raised in the CNS of diseased animals, whilst dramatic therapeutic benefits are witnessed ‘in vitro’ when TSE affected cell cultures are treated with these molecules. It seems likely that the normal cellular form of PrP (PrPc) binds with a specific co-species of glycoaminoglycans ‘in vivo’, which might serve as a means of protecting PrPc against conversion into its abnormal TSE isoform. This hypothesis proposes that CNS Cu deficiency is integral to the aetiology of TSEs, where the depleted supply of Cu to PrP’s Cu domain renders the protein vulnerable to invasion with alternative cations, such as Mn, which could ligate to the Cu domain and lead to the development of the misfolded, pathogenic prion associated with TSE.
CNS Cu deficiency can be invoked via various naturally occurring or artificially invoked mechanisms, or combinations thereof:

1. due to indigenous copper deficiency in the external food chain (influenced by seasonal, climatic and/or other geological (3, 4, 31) characteristics such as high soil molybdenum levels).

2. due to an oxidant mediated upregulation of the expression of Cu-metalloproteins, such as PrP, placing demands on the supply of available Cu in the CNS (32, 15, 33, 34).

3. due to chelation of available Cu in the CNS by certain foreign organo pollutants (21).

4. due to the inhibitory effects placed on Cu absorption by excesses of Ca or estrogens (35, 36) as in feeds such as alfalfa/soya respectively.

5. due to the accelerated excretion of Cu resulting from therapeutic treatment with steroids, etc (37). due to a foreign organic pollutant induced covalent modification of (or binding to) the active histidine/tyrosine residues (10 p45) (12) (38) (39) on PrP’s Cu domain; thereby preventing Cu from accessing its binding domain on PrP (15, 34).

Experimental evidence indicates a role for PrP's Cu domain in protecting the cell against oxidative stress; via a PrP-mediated regulation of SOD1 activity.

        D Brown and others have provided strong ‘in vitro’ and ‘in vivo’ experimental evidence that supports a functional role for PrPc in protecting CNS cerebellar cells against the deleterious impact of oxidative stress (33). Treatment with the antioxidant vitamin E has also been shown to protect cells lacking PrP expression against oxidant mediated cell death (33).
        Brown proposes that PrPc influences the activity of SOD1 (40) and points to the Cu domain that has been identified at the N terminal octapeptide repeat region of PrP (15, 34) , suggesting that PrP may perform a role in the transportation of Cu to the sites of SOD 1 synthesis, Cu and Zn act as co factors in the synthesis of the SOD 1 superoxide scavenger. Mice devoid of PrP due to genetic ablation demonstrate a reduced resistance to oxidative stress. Cu and Zn act as co factors in the synthesis of the SOD 1 superoxide scavenger. Mice devoid of PrP due to genetic ablation demonstrate a reduced resistance to oxidative stress.

The key biochemical and pathological facets of TSE suggest a pivotal role of oxidative stress in TSE pathogenesis.

        The biochemistry, pathology and distribution of CNS abnormalities associated with the pathogenesis of TSEs suggests that oxidative stress plays a major aetiological role in TSEs;
        Decreased amounts of phospholipids and gangliosides/increased levels of cholesterol in membranes (41, p.100), an abundance of lipofuscin inclusions in neurones (42), an upregulation of the signal transduction cycle and kinase C phosphorylation, increases in intraneuronal free calcium (43, 44), reduction in monamine oxidase/NAD diaphorase (45,46), an increase in citrulline/ornithine in blood sera (47), a decrease in membrane fluidity (41, p.106), rupturing of lysosomal membranes (46), an excessive CNS accumulation of iron in its Ferritin form (29), and a marked increase in multimeric mitochondrial DNA/DNA strand breakage (48). All of these abnormalities are characteristic of free radical disturbances (10, 49-52) and are shared in the pathogenesis of other neurodegenerative diseases similar to TSEs such as Parkinsons (PD), Alzheimer’s (AD) and Motor Neurone Disease (MND) - diseases which are now recognised to stem from a free radical-mediated pathogenesis (52, 53).
        It is proposed that the different ‘strains’ of TSEs may be caused by different species of radical-generating divalent cation (Mn, Nickel, Fe or cobalt, etc.) that can successfully compete and ligate at PrP’s Cu domain during states of Cu deficiency. The greater the oxidative capacity of the metal species involved (e.g. Mn3+, Mn4+ or even radioactive species), the more virulent strain of TSE to emerge. This aetiological model operates in combination with various other multifactorial criteria:

1. The duration and intensity of exposure to the different classes of divalent cation/organic chemical pollutant in the environment, (more directly related to the particular species of radical that they generate).
2. The TSE-susceptibility of the exposed individual; relating to their PRP (41)/SOD 1,2,3/ceruloplasmin/cytochrome P450 genotype.
3. Other external environmental variables which can ultimately influence the CMS uptake of Mn, e.g.:
   1. low Fe,
   2. levels of stress or environmental pollutants which mediate ACTH turnover, blood-brain barrier homeostatis and Mn uptake in CNS.
   3. Daylight interval in relation to the untra violet mediated regulation of melatonin turn over, which, in turn, mediates estrogen/corticosteroid turn over and Mn uptake.
   4. levels of estrogenic/steroid pollutants in the environment (4,54) and their ability to upregulate the expression of caeruloplasmin (55) which can lead to oxidation of increased amounts of Mn2+ into its more lethal Mn3+ species (7), particularly in the absence of its normal oxidation target, Fe2+.

4. The developmental stage of the victim during intoxication (56).

   SPORADIC TSEs - AN ANALYTICAL SURVEY INTO THE LEVELS OF METALS IN ECOSYSTEMS SUPPORTING CLUSTERS OF TSE: DESIGN

   Foodchains supporting isolated, long standing clusters of sporadic TSEs were sampled by the author for analysis of mineral status in order to ascertain whether any elemental deficiencies or toxic excesses are common idiosncratic characteristics of these TSE foci, Adjoining TSE-free regions populated by significant numbers of the respective species associated with thee study were sampled as controls.
           The TSE clusters of chronic wasting disease (CWD) in wild deer/elk in N. Central Colorado (57,58), sheep scrapie in N Iceland (59,60) and CJD in Slovakia (61-64) were selected for this survey for various reasons:

   1. A long history of TSE being confined to specific well-defined regions.
   2. The dependence of TSE affected populations on the local foodchain.
   3. The relative freedom of those foodchains (excluding the Slovakia TSE foci) from excessive contamination by synthetic pro-oxidant industrial/agricultural pollutants which would complicate the study.

           The repeated failure of various Government TSE eradication programmes executed in the TSE endemic regions of Colorado/Iceland (57,59) - involving blanket slaughter, 4 year fallow, then restocking - suggests the persistent presence of a hitherto unrecognized environmental causal factor common to these regions.
           It is worth noting that high altitude, snow covered peaked mountain ranges of volcanic origin - with an abundance of coniferous trees - characterize the environments where sporadic TSE foci have traditionally arisen. This could be linked to the annual spring snow thaw and the resulting waterlogging of soils; where the main minerals utilized as antioxidant cofactors in biological systems are leached out of the soil, whilst others, like manganese/aluminium, readily accumulate in the plant horizon as a result of the temporary acidification of the soils due to increases in anaerobic conditions during the wet season.
           Furthermore, the hypoxia of high-altitude lining increases susceptibility to oxidative stress and increases permeability of the brain barrier to cations, etc.

   MATERIALS AND METHODS: SOIL

Each soil sample comprised a representative sample drawn from a mix of approximately 20 slices of dry soil dug with a stainless steel trowel and taken at equal spacings along a W shape spanning an area of approximately five acres; the area being representative of the region grazed/cropped by the TSE affected mammals under study.
        Each slice was drawn from the top soil to a depth of 6 inches, if possible, taking care to avoid inclusion of root material/surface organic matter and drawing of samples near gateways, roadsides, animal dung, disturbed/excavated or polluted terrain, etc.
        The 20 slices were put into plastic bags and mixed together into an even homogenate, from which a further sample of no more than 300 g was drawn and placed into a small cardboard box which was sealed, labelled and dispatched to the UK Laboratories of Natural Resources Management (NRM), Coopers Bridge, Braziers Lane, Bracknell, Berkshire, RG42 6NS.
        Soil samples were laid out on drying trays after arriving at the laboratory and dried in forced air flow cabinets for 12-18 h until dry. The temperature was maintained below 32° for this period and the air was constantly dehumidified. Any solid rock granules were removed from samples before being ground to pass a 2 mm mesh using a hammer mill. The mill was flushed between samples using a small portion of the next sample. Samples required for total mineral analysis were subsequently ground to pass a 0.5 mm mesh. Samples were then presented for analysis - the analytical procedures for each mineral are described on Table 3, which were conducted in accord with the standard analysis procedure of the Ministry of Agriculture, Fisheries and Food.
        Each plant tissue sample comprised a 200g sample representing tissue collected from approximately 10 pickings taken at equal spacings in a W shape across an area of approx five acres which was representative of the region grazed/cropped by the TSE mammals under study.
        Each picking involved taking tissue (leaves, stem and flowerheads) from the upper half of the plant, and involved species of grasses, plants and/or shrubs that commprised the overall dietary intake of the mammals under study according to local intelligence.
        Samples were picked dry and away from roadsides, gateways, animal manure, polluted or disturbed terrain, whilst care was taken to avoid the inclusion of any root material or soil. The tissue was packed into plastic bags which were lightly sealed, labelled accordingly and dispatched to the laboratories of NRM.
        Samples were thoroughly washed with deionised water, in a plastic sieve, on arrival at NRM Ltd. After removal of all roots and soil, the samples were spread evenly on a drying tray and dried in a 90 degree C oven to constant weight, and then ground by a Christy Norris mill. A small portion of the sample was used to flush the mill, before collection of the ground material. The samples were then prepared for analysis by dry ashing for non-volatile elements and wet digestion in aqua/regia for volatile elements (e.e. selenium, etc).
        The analytical procedures for each mineral is listed on Table 1, and these were carried out in accord with MAFF's standard analysis method.

RESULTS: HIGH LEVELS OF MN CATION FOUND IN TSE ASSOCIATED FOODCHAINS
 
1. Icelandic scrapie cluster
 
The scrapie endemic valleys in North Central/Eastern Iceland where sheep have suffered from a high incidence of scrapie for many decades demonstrated a consistent two and a half fold greater concentration of the divalent cation, manganese, in herbage at 200 mg/kg dry basis in relation to the 80 mg/kg average level found in the regions where scrapie has never been recorded (Table 1) (Fig.2).
        This could be part related to the higher intensity of precipitation/snow cover (e.g., perhaps linked to the eco-impact of the annual snow thaw run off) recorded in the scrapie endemic regions (personal communication; S. Sigurdarson)in combination with the high organic matter content of the peat soils which favours increased waterlogging and soil acidity, rendering Mn more freely available for plant uptake (31, p. 14/15/166).
        Furthermore, the snow cover and short daylight interval of the Icelandic winters could favour an increased amount of Mn in herbage tissue in line with the recorded effects of shade on increasing the Mn content of leaves (65).

2     Vidivellir

1.56

0.20

1.26

0.19

0.57

89    

2.4

0.05

118      

32.7    

2.68

0.018

0.15

3     Desjarmyri

2.35

0.28

1.40

0.24

0.39

228  

3.4

0.32

599      

47.6    

0.56

0.032

0.40

4     Hrafnabjorg

3.15

0.36

1.63

0.24

0.44

107  

5.0

0.06

164      

27.8    

0.41

0.012

0.28

5     Hofsa

2.64

0.30

1.33

0.18

0.41

144  

4.7

0.12

389      

34.0    

0.73

0.055

0.32

6     Ingvarir (M)

1.88

0.21

1.17

0.17

0.40

297  

3.5

0.05

942      

32.9    

1.07

0.051

0.59

7     Ingvarir (L)

2.85

0.29

0.90

0.31

0.90

145  

4.3

0.35

132      

17.5    

3.29

0.029

1.61

8     Ingvarir (H)

1.06

0.10

0.81

0.12

0.26

277  

1.2

0.01

151      

18.2    

0.48

0.010

0.25

9     pvera (M)

3.53

0.37

2.47

0.24

0.47

275  

5.9

0.10

611      

44.7    

0.92

0.037

0.58

9     pvera (L)

1.62

0.17

1.05

0.20

0.60

245

2.3

0.02

213      

31.6    

0.62

0.110

0.42

11   pvera (H)

1.61

0.10

0.75

0.16

0.40

127

2.3

0.01

846      

21.9    

0.64

0.002

0.95

12   Atlastadir

1.58

0.20

0.94

0.21

0.46

310  

3.0

0.03

192      

20.7    

0.17

0.011

0.13

13   Vigdisarstadir

3.30

0.32

0.58

0.34

0.51

210  

6.5

0.24

271      

28.3    

1.26

0.010

0.46

Av scrapie

2.26

0.24

1.24

0.22

0.50

200 

3.4

0.10

373      

30.5    

0.99

0.032

0.50

Category

mean

low

mean

low

mean

high

very
low

very
low

mean

low

mean
low

very
low

high

Scrapie-free

14   Hjalp

1.73

0.21

1.18

0.29

0.84

89     

2.3

0.03

303      

34.4    

0.51

0.077

0.40

15   Holmar

1.81

0.24

1.21

0.14

0.28

67    

3.8

0.10

1285      

24.2    

2.20

0.021

0.76

16   Kvisker

2.10

0.25

1.62

0.38

0.77

100

3.2

0.08

98      

122.3    

0.86

0.030

0.16

17   Modruvellir

3.47

0.33

2.36

0.25

0.37

76     

6.2

0.00

89      

23.9    

0.64

0.010

0.09

18   Modruvellir

2.52

0.28

2.34

0.17

0.31

69     

6.2

0.01

61      

14.2    

0.38

0.010

0.23

19   Brakandi

1.90

0.18

1.71

0.17

0.33

96     

2.1

0.00

85      

16.4    

1.26

0.020

0.14

20   Skriduklaustur

2.27

0.28

2.09

0.23

0.65

67     

4.1

0.02

131      

37.2    

2.06

0.010

0.56

Av Sc-free

2.26

0.25

1.79

0.23

0.50

80    

4.0

0.03

293      

39.0    

1.13

0.025

0.33

Category

mean

low

mean

low

mean

mean

low

very
low

mean

low

mean

very
low

high

Scrapie ?? in scrapie-endemic zone

21   Sakka

3.41

0.35

1.88

0.23

0.48

179

6.1

0.11

417      

48.5    

1.88

0.020

0.43

22   Brautarholl

2.28

0.26

1.35

0.21

0.52

235  

3.3

0.06

93      

23.0    

0.84

0.010

0.11

23   Barka

2.85

0.34

1.65

0.20

0.39

135  

3.6

0.02

153      

33.1    

0.84

0.023

0.10

Av Sc??

2.85

0.31

1.62

0.21

0.46

183  

4.3

0.06

221      

34.8    

1.18

0.017

0.21

Category

mean

mean

mean

low

mean

high

low

very
low

mean

low

mean

very
low

high

Fig. 2   Map of Iceland depicting sample sites and main scrapie endemic region (hatched). Numbered sample sites correspond to numbering of farms on Table 1.

Fig. 3   Map of Larimer County in Colorado Depicting location of sample sites across CWD endemic cluster region and where CWD affected cervidae have been found (58). Numbered sample sites correspond to numbering of locations on Table 3. Shaded circles represent CWD affected deer. Hatched circles represent CWD affected elk.

  Interestingly, there are some good examples of scrapie-free valleys found in the middle of the scrapie endemic zones which provide good opportunities for comparative studies. One fascinating example is demonstrated NW of Akureyri where the scrapie endemic valley 'Svarfadardalur' runs 15 miles parallel to the scrapie free valley 'Horgardalur' (see Fig. 3). Sheep from both valleys freely intermingle on the open mountain during summertime, suggesting that the mystery causal factor X associated with scrapie aetiology would be present in the specific valley homes where the scrapie affected flocks overwinter. Results of the author's study demonstrated an av level of 94 mg/kg Mn (dry basis) drawn from 4 test sites in the scrapie free valley and 223.4 mg/kg Mn from 10 sites in the scrapie valley. Interestingly, Barka was the only farm recorded in the scrapie free valley that has purportedly suffered a suspected outbreak of scrapie in 1949, perhaps explaining why the Barka sample demonstrated the highest Mn level in the valley:
 

CWD region

1     Horsetooth

1.66

1.89

0.77

5.8

84.8

0.10

.080

.15

.2

 38

.01

19.0  

.090

  5     Owl Canyon

2.63

1.46

2.04

9.1

80.7    

2.03

.250

.21

.40

30

.01

19.2    

36.6

.160

  6     Poudre Canyon

1.54

1.67

0.76

5.0

69.7    

0.16

.240

.19

.18

37

.00

19.7    

19.6

.110

  7     Teds Place

5.03

5.81

2.05

7.1

194.8    

1.68

.065

.40

.40

44

.01

25.9    

42.9

.220

  9     Black Canyon

2.21

1.83

0.71

6.6

365.7    

1.06

.064

.26

.16

50

.00

105.7    

18.2

.040

12     H-Bar-G Ranch

1.76

1.92

0.83

5.6

131.9    

1.16

.270

.24

.19

38

.00

45.0    

21.9

.050

        Av CWD

2.47

2.43

1.19

6.5

154.6    

1.03

.161

.24

.25

40

.005

39.0    

26.5

.111

Category

mean

mean

very
high

low

mean

mean

low

low

low

mean

very
low

low

mean

mean

CWD ZONE COLORADO

(1997)

 1     Horsetooth Mt

7.0

6.0

250

309   

1.4

0.7

3.3

1.0

2576

0.0

14   

36.7 

.09 

6.4  

333  

  2     Spring Creek

6.6

3.8   

115

167   

1.3

0.4

2.4

0.9

1541

0.1

28   

23.1

.18

15.0   

261   

  3     Horsetooth Re

6.8

4.0   

101

280   

0.8

0.5

3.5

0.9

1635

0.1

22   

27.1

.24

8.0   

300   

  4     Livermore

8.7

5.4   

290

72   

1.0

0.8

1.4

1.1

2833

0.0

2   

34.4

.09

2.0   

373   

  5     Owl Canyon

8.6

6.0   

221

153   

0.8

0.7

5.2

0.9

3777

0.1

11   

32.9

.18

5.0   

229   

  6     Poudre Canyon

7.4

7.4   

247

97   

2.7

0.7

2.0

2.8

1512

0.0

16   

24.1

.10

9.0   

465   

  7     Teds Corner

6.8

25.4   

506

99   

2.5

0.8

3.9

3.0

2251

0.1

37   

33.2

.19

18.0   

320   

  8     Bellvue

8.3

29.2   

236

248   

2.1

1.0

9.9

1.7

3295

0.1

9   

42.9

.13

3.0   

99   

  9     Black Canyon

6.7

29.4   

395

170   

3.8

0.8

4.3

9.1

1418

0.3

50   

21.9

.16

20.0   

329   

10     Black Canyon

6.4

5.6   

175

146   

0.9

0.5

3.1

1.5

1822

0.3

51   

19.2

.16

10.0   

468   

11     H-Bar-G Ranch

6.6

6.6   

249

150   

1.3

0.5

1.9

0.8

1194

0.1

29   

17.0

.06

7.0   

341   

12     H-Bar-G Ranch

6.5

4.8   

167

110   

1.4

0.5

3.5

2.9

1260

0.1

38   

18.7

.12

8.0   

293   

        Av CWD

7.2

10.6   

246

166   

1.6

0.6

3.7

2.2

2093

0.1

25   

27.6

.14

9.3   

317   

        Category

high

low

mean

mean

very
low

low

very
low

mean

mean

low

high

mean

low

mean

very high

CWD-FREE UTAH

Gt Cottonwood

7.6

11.4   

194

177   

10.7   

0.6

275

61   

2056

0.2

52   

67.7

.26

25.0   

Lt Cottonwood

7.2

9.4   

 91

75   

5.1   

x

x

8   

x

1.3

88   

x

x

32.0   

Av CWD-free

7.4

10.4   

142

126   

7.9   

0.6

275

35   

2056

0.7

70   

67.7

.26

25.0   

Category

mean

low

low

mean

high

low

high
high

very

mean

mean
high

very
high

very
high

mean

high

Matrix 1 - Natural uncultivated pasture

Test Site

P%

K%

Mg%

Ca%

Mn

Cu

Na%

Fe

Zn

Mo

Se

Al

Co

S%

Ni

Ti

CJD Endemic (Orava cluster)

Zuberec

.12

1.01

.23

0.94

437   

5.9

.01

83.5   

74.2

3.0

0.052

84.4   

.34

.20

4.35   

1.35

Huty

.19

1.82

.26

1.85

86   

8.1

.01

87.1   

40.9

3.8

0.043

108.5   

.17

.32

1.50   

0.30

Malatina

.28

2.20

.28

1.58

115   

9.9

.01

119.6   

39.6

2.6

0.043

115.2   

.19

.25

5.41   

1.41

Pucov

.20

1.98

.27

1.99

204   

6.9

.01

111.6   

33.2

0.8

0.041

102.6   

.23

.19

10.8   

1.41

Av CJD

.19

1.75

.26

1.59

210   

7.7

.01

100.4   

46.2

2.5

0.044

102.7   

.23

.24

5.51   

1.06

Scale

low

norm

low

very high

high

low

very
low

low

low

norm

very
low

?

high

?

CJD-free    (Poprad)

Poprad S

.41

2.64

.34

1.57

85   

15.

.02

166.0   

34.2

0.6

0.032

182.4   

.31

.37

23.3   

4.18

Scale

high

norm

norm

very high

norm

high

very
low

norm

low

norm

very
low

?

high

?

Matrix 2 - Pine needles

CJD Endemic (Orava cluster)

Zuberec

951   

3.9

104   

52.3

103.0   

33.5   

1.23

very high

very
low

low

norm

CJD-free    (Poprad)

Vernar

59   

3.2

113   

57.1

76.7   

19.2   

1.98

mean

very
low

low

norm

P%

0.35 (0.4)

0.29

0.30

0.26 (.04)

0.32